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Dr Raymond Chiong

Senior Lecturer

School of Design Communication and IT (Information Technology)

Career Summary

Biography

Raymond graduated with a PhD degree from the University of Melbourne. He has taught a variety of undergraduate and postgraduate courses in the areas of computer science and information systems at Swinburne University of Technology for almost a decade before joining the University of Newcastle, Australia, in early 2013. Besides teaching, he has been actively pursuing research related to evolutionary game theory, optimisation, data analytics, and modelling of complex adaptive systems, with applications in areas such as production scheduling, energy load forecasting, social behaviour modelling and marketing. He is a member of the Scientific Advisory Board of Complexica, an Artificial Intelligence software company that helps large organisations sell more products and services, and reduce their labour costs and headcount through the use of automated analytics.

Raymond served as the Editor-in-Chief of the Interdisciplinary Journal of Information, Knowledge, and Management from 2011 to 2014. Currently, he is an Editor for the journal Engineering Applications of Artificial Intelligence and an Associate Editor for the IEEE Computational Intelligence Magazine. He has also served in a Guest Editor role for a number of reputable international journals, such as the International Journal of Production Economics and European Journal of Operational Research. He was the Vice Chair of the task force “Education” of IEEE Computational Intelligence Society’s Emergent Technology Technical Committee, and one of the Founding co-Chairs of the IEEE Symposium on Computational Intelligence in Production and Logistics Systems.

To date, Raymond has produced/co-authored over 100 refereed publications in the form of books, book chapters, journal articles and conference papers, among others.

Research Expertise

  • Evolutionary optimisation
  • Evolutionary game theory
  • Data analytics and machine learning
  • Modelling of complex adaptive systems
  • Technology enhanced learning 

Teaching Expertise

Courses coordinated and taught at the University of Newcastle:

  • INFO6801 Information Technology Research Methods (postgraduate)
  • INFO6101 Information Technology Research I (postgraduate)
  • INFO6102 Information Technology Research II (postgraduate)
  • INFO6030 Systems Analysis and Design (postgraduate)
  • INFT2012 Applications Programming
  • INFO1010 Introduction to Information Systems and Technology
  • EBUS2000 Information and Communication in Business

Units convened and taught at Swinburne University of Technology:

  • MTB610 Data Management and Business Intelligence (postgraduate)
  • MTB520 Systems Development (postgraduate)
  • CIS13 Information Systems and Fundamentals
  • CIS100 Programming Concepts
  • HIT3181 Technical Software Development
  • HIT3172 Object-oriented Programming in C++
  • HIT2080 Introduction to Programming (in C)
  • HIT3002 Introduction to Artificial Intelligence
  • HIT2420 Database Management Systems
  • HIT2405 Requirement Analysis and Modelling
  • HIT1402 Database Analysis and Design

Collaborations

The University of Melbourne -- working with Assoc Prof Michael Kirley on evolution of (N-player) cooperation using evolutionary computation and agent-based modelling techniques.

Selected publications:

  • R. Chiong and M. Kirley, "Promotion of cooperation in social dilemma games via generalised indirect reciprocity," Connection Science, vol. 27(4), pp. 417-433, 2015. See http://dx.doi.org/10.1080/09540091.2015.1080226
  • R. Chiong and M. Kirley, "Effects of iterated interactions in multi-player spatial evolutionary games," IEEE Transactions on Evolutionary Computation, vol. 16(4), pp. 537-555, 2012. See http://dx.doi.org/10.1109/TEVC.2011.2167682
  • R. Chiong and M. Kirley, "Random mobility and the evolution of cooperation in spatial N-player iterated prisoner's dilemma games," Physica A: Statistical Mechanics and its Applications, vol. 391(15), pp. 3915-3923, 2012. See http://dx.doi.org/10.1016/j.physa.2012.03.010

University of Science and Technology of China -- working with Assoc Prof Thomas Weise and his students on optimisation and algorithm benchmarking using evolutionary computation and local search methods.

Selected publications:

  • T. Weise, Y. Wu, R. Chiong, K. Tang and J. Lässig, "Global versus local search: The impact of population sizes on evolutionary algorithm performance," Journal of Global Optimizationhttp://dx.doi.org/10.1007/s10898-016-0417-5
  • T. Weise, R. Chiong, J. Lässig, K. Tang, S. Tsutsui, W. Chen, Z. Michalewicz and X. Yao, "Benchmarking optimization algorithms: An open source framework for the traveling salesman problem," IEEE Computational Intelligence Magazine, vol. 9(3), pp. 40-52, 2014. See http://dx.doi.org/10.1109/MCI.2014.2326101
  • T. Weise, R. Chiong and K. Tang, "Evolutionary optimization: Pitfalls and booby traps," Journal of Computer Science and Technology, vol. 27(5), pp. 907-936, 2012. See http://dx.doi.org/10.1007/s11390-012-1274-4

Huazhong University of Science and Technology, China -- working with Prof Yukun Bao and his team (including Dr Zhongyi Hu, who is now with Wuhan University) on forecasting of electricity loads and stock prices using machine learning and evolutionary computation methods.

  • Z. Hu, Y. Bao, R. Chiong and T. Xiong, "Mid-term interval load forecasting using multi-output support vector regression with a memetic algorithm for feature selection," Energy, vol. 84, pp. 419-431, 2015. See http://dx.doi.org/10.1016/j.energy.2015.03.054
  • Z. Hu, Y. Bao, T. Xiong and R. Chiong, "Hybrid filter-wrapper feature selection for short-term load forecasting," Engineering Applications of Artificial Intelligence, vol. 40, pp. 17-27, 2015. See http://dx.doi.org/10.1016/j.engappai.2014.12.014
  • T. Xiong, Y. Bao, Z. Hu and R. Chiong, "Forecasting interval time series using a fully complex-valued RBF neural network with DPSO and PSO algorithms," Information Sciences, vol. 305, pp. 77-92, 2015. See http://dx.doi.org/10.1016/j.ins.2015.01.029

Tsinghua University/Xiamen University of Technology, China -- working with Prof Shiji Song, Prof Rui Zhang and Jian-Ya Ding on (sustainable) production scheduling using both evolutionary computation and operations research methods.

  • J.-Y. Ding, S. Song, R. Zhang, R. Chiong and C. Wu, "Parallel machine scheduling under time-of-use electricity prices: New models and optimization approaches," IEEE Transactions on Automation Science and Engineering, vol. 13(2), pp. 1138-1154, 2016. See http://dx.doi.org/10.1109/TASE.2015.2495328
  • R. Zhang and R. Chiong, "Solving the energy-efficient job shop scheduling problem: A multi-objective genetic algorithm with enhanced local search for minimizing the total weighted tardiness and total energy consumption," Journal of Cleaner Production, vol. 112, pp. 3361-3375, 2016. See http://dx.doi.org/10.1016/j.jclepro.2015.09.097
  • J.-Y. Ding, S. Song, J. N. D. Gupta, R. Zhang, R. Chiong and C. Wu, "An improved iterated greedy algorithm with a Tabu-based reconstruction strategy for the no-wait flowshop scheduling problem," Applied Soft Computing, vol. 30, pp. 604-613, 2015. See http://dx.doi.org/10.1016/j.asoc.2015.02.006

Qualifications

  • Doctor of Philosophy, University of Melbourne
  • Master of Science, University of Birmingham - UK

Keywords

  • Evolutionary computation
  • Evolutionary game theory
  • Machine learning and data mining
  • Modelling of complex systems

Fields of Research

Code Description Percentage
080102 Artificial Life 20
080108 Neural, Evolutionary and Fuzzy Computation 60
080199 Artificial Intelligence and Image Processing not elsewhere classified 20

Professional Experience

UON Appointment

Title Organisation / Department
Senior Lecturer University of Newcastle
School of Design Communication and IT
Australia

Academic appointment

Dates Title Organisation / Department
1/03/2014 -  Guest Research Professor Huazhong University of Science And Technology
China
18/07/2005 - 31/01/2013 Lecturer Swinburne University of Technology, VIC
Australia

Membership

Dates Title Organisation / Department
26/06/2014 -  IEEE Senior Member Institute of Electrical & Electronic Engineers (IEEE)
Australia

Awards

Nomination

Year Award
2015 NSW Young Tall Poppy Science Award
Australian Institute of Policy & Science (AIPS)
2015 Faculty Award for Research and Innovation Excellence
Faculty of Science and Information Technology, The University of Newcastle | Australia

Invitations

Distinguished Visitor

Year Title / Rationale
2016 Visiting Scholar under the Short-term Exchange and Cooperation of Well-known Overseas Scholars program, Tsinghua University

Keynote Speaker

Year Title / Rationale
2015 ACM SIGKDD Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM 2015)
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Publications

For publications that are currently unpublished or in-press, details are shown in italics.


Book (9 outputs)

Year Citation Altmetrics Link
2014 Catay B, Chiong R, Siarry P, Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems, IEEE Press, Piscataway, NJ, 165 (2014)
2013 Chiong R, Weise T, Michalewicz Z, Variants of evolutionary algorithms for real-world applications (2013)

© 2012 Springer-Verlag Berlin Heidelberg. All rights are reserved.Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. D... [more]

© 2012 Springer-Verlag Berlin Heidelberg. All rights are reserved.Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book "Variants of Evolutionary Algorithms for Real-World Applications" aims to promote the practitioner's view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter re-visiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the prediction of soil properties, automated tissue classification for MRI images, and database query optimisation, among others. These chapters demonstrate how different types of problems can be successfully solved using variants of EAs and how the solution approaches are constructed, in a way that can be understood and reproduced with little prior knowledge on optimisation.

DOI 10.1007/978-3-642-23424-8
2013 Jovanovic J, Chiong R, Technological and Social Environments for Interactive Learning, Informing Science Press, Santa Rosa, CA, 492 (2013) [A3]
2013 Catay B, Chiong R, Siarry P, Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems, IEEE Press, Piscataway, NJ, 145 (2013)
2011 Catay B, Chiong R, Siarry P, Proceedings of the 2011 IEEE Workshop on Computational Intelligence in Production and Logistics Systems, IEEE Press, Piscataway, NJ, 67 (2011)
2010 Chiong R, Nature-inspired informatics for intelligent applications and knowledge discovery: Implications in business, science, and engineering, IGI Global, Hershey, PA (2010)
DOI 10.4018/978-1-60566-705-8
2010 Chiong R, Intelligent systems for automated learning and adaptation: Emerging trends and applications, IGI Global, Hershey, PA (2010)
DOI 10.4018/978-1-60566-798-0
2009 Chiong R, Nature-Inspired Algorithms for Optimisation, Springer-Verlag, Berlin, Germany, 514 (2009) [A3]
2009 Chiong R, Dhakal S, Natural Intelligence for Scheduling, Planning and Packing Problems, Springer Science & Business Media, Berlin-Heidelberg, 329 (2009)
Show 6 more books

Chapter (11 outputs)

Year Citation Altmetrics Link
2013 Blum C, Chiong R, Clerc M, De Jong K, Michalewicz Z, Neri F, Weise T, 'Evolutionary optimization', Variants of Evolutionary Algorithms for Real-World Applications 1-29 (2013)

© 2012 Springer-Verlag Berlin Heidelberg. All rights are reserved. The emergence of different metaheuristics and their new variants in recent years has made the definition of the... [more]

© 2012 Springer-Verlag Berlin Heidelberg. All rights are reserved. The emergence of different metaheuristics and their new variants in recent years has made the definition of the term Evolutionary Algorithms unclear. Originally, it was coined to put a group of stochastic search algorithms that mimic natural evolution together. While some people would still see it as a specific term devoted to this group of algorithms, including Genetic Algorithms, Genetic Programming, Evolution Strategies, Evolutionary Programming, and to a lesser extent Differential Evolution and Estimation of Distribution Algorithms, many others would regard "Evolutionary Algorithms" as a general term describing population-based search methods that involve some form of randomness and selection. In this chapter, we re-visit the fundamental question of "what is an Evolutionary Algorithm?" not only from the traditional viewpoint but also the wider, more modern perspectives relating it to other areas of Evolutionary Computation. To do so, apart from discussing the main characteristics of this family of algorithms we also look at Memetic Algorithms and the Swarm Intelligence algorithms. From our discussion, we see that establishing semantic borders between these algorithm families is not always easy, nor necessarily useful. It is anticipated that they will further converge as the research from these areas cross-fertilizes each other.

DOI 10.1007/978-3-642-23424-8_1
Citations Scopus - 9
2013 Moser I, Chiong R, 'Dynamic function optimization: The moving peaks benchmark', Metaheuristics for Dynamic Optimization, Springer, Berlin 35-59 (2013) [B1]
DOI 10.1007/978-3-642-30665-5_3
Citations Scopus - 4
2010 Su SI, Chiong R, 'Business intelligence', Encyclopedia of Knowledge Management 72-80 (2010)
DOI 10.4018/978-1-59904-931-1.ch008
Citations Scopus - 6
2010 Chiong R, Neri F, McKay RI, 'Nature that breeds solutions', Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, IGI Global, Hershey, PA 1-24 (2010)
DOI 10.4018/978-1-60566-705-8.ch001
Citations Scopus - 11
2010 Weise T, Chiong R, 'Evolutionary approaches and their applications to distributed systems', Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications, IGI Global, Hershey, PA 114-149 (2010)
DOI 10.4018/978-1-60566-798-0.ch006
Citations Scopus - 2
2009 Weise T, Zapf M, Chiong R, Nebro AJ, 'Why is optimization difficult?', Nature-Inspired Algorithms for Optimisation, Springer, Berlin-Heidelberg 1-50 (2009) [C3]
DOI 10.1007/978-3-642-00267-0_1
Citations Scopus - 16
2009 Chiong R, 'Teaching machines to find names', Encyclopedia of Artificial Intelligence, Information Science Reference, Hershey, PA 1562-1567 (2009)
2009 Chiong R, 'Distance learning concepts & technologies', Encyclopedia of Multimedia Technology and Networking, Information Science Reference, Hershey, PA 417-422 (2009)
2008 Chiong R, 'Evolving cooperative agents in economy market using genetic algorithms', Success in Evolutionary Computation, Springer, Berlin-Heidelberg 313-326 (2008) [C2]
DOI 10.1007/978-3-540-76286-7_14
2008 Chiong R, Jankovic L, 'Agent strategies in economy market', Applications of Complex Adaptive Systems 1-33 (2008)

This chapter presents a method on modelling the economy market using agent-based representation and iterated prisoner's dilemma (IPD). While IPD has been used widely in various ec... [more]

This chapter presents a method on modelling the economy market using agent-based representation and iterated prisoner's dilemma (IPD). While IPD has been used widely in various economic problems, most of the studies were based on quantitative data which could be deductive and inappropriate. The main objective of this chapter is to present a unique agent-based approach which places lower demand on data using IPD to model the complexity of the economy market. We create a simulated market environment with agents acting as firms to perform transactions among each other with chosen IPD strategy. From empirical results, we investigate strategic interactions among different firms. In the concluding remarks, we present our observations on the qualities of a winning strategy. © 2008, IGI Global.

DOI 10.4018/978-1-59904-962-5.ch001
2007 Issac B, Mering J, Chiong R, Jacob SM, Then P, 'E-learning implementation and its diverse effects', Information Technology and Economic Development 260-277 (2007)

The rapid growth of technological advances in recent years has opened a completely new dimension to progress in education and training. The emergence of e-learning has created not... [more]

The rapid growth of technological advances in recent years has opened a completely new dimension to progress in education and training. The emergence of e-learning has created not only business and educational opportunities, but also significantly improved the standard of the society. This chapter explores the implementation of e-learning and its impact on a community, similar to a university or corporate setup. To this aim, a brief introduction into e-learning technology and an example of using the Blackboard Learning System are brought forth, along with some critical success factors. Projecting the e-learning advantages along with the digital library concepts, the economic benefits of such implementation are highlighted. The discussion then moves to the perspective of students and teachers on e-learning. As the trend in the technological world is moving toward mobility, the wireless e-learning perception is also conferred. In the concluding remarks, e-learning implementation is noted as a positive endeavor to boost economic growth. © 2008, IGI Global.

DOI 10.4018/978-1-59904-579-5.ch019
Show 8 more chapters

Journal article (42 outputs)

Year Citation Altmetrics Link
2016 Ding JY, Song S, Zhang R, Chiong R, Wu C, 'Parallel Machine Scheduling Under Time-of-Use Electricity Prices: New Models and Optimization Approaches', IEEE Transactions on Automation Science and Engineering, 13 1138-1154 (2016)

© 2015 IEEE.The industrial sector is one of the largest energy consumers in the world. To alleviate the grid's burden during peak hours, time-of-use (TOU) electricity pricing has... [more]

© 2015 IEEE.The industrial sector is one of the largest energy consumers in the world. To alleviate the grid's burden during peak hours, time-of-use (TOU) electricity pricing has been implemented in many countries around the globe to encourage manufacturers to shift their electricity usage from peak periods to off-peak periods. In this paper, we study the unrelated parallel machine scheduling problem under a TOU pricing scheme. The objective is to minimize the total electricity cost by appropriately scheduling the jobs such that the overall completion time does not exceed a predetermined production deadline. To solve this problem, two solution approaches are presented. The first approach models the problem with a new time-interval-based mixed integer linear programming formulation. In the second approach, we reformulate the problem using Dantzig-Wolfe decomposition and propose a column generation heuristic to solve it. Computational experiments are conducted under different TOU settings and the results confirm the effectiveness of the proposed methods. Based on the numerical results, we provide some practical suggestions for decision makers to help them in achieving a good balance between the productivity objective and the energy cost objective.

DOI 10.1109/TASE.2015.2495328
2016 Weise T, Wu Y, Chiong R, Tang K, Lässig J, 'Global versus local search: the impact of population sizes on evolutionary algorithm performance', Journal of Global Optimization, 1-24 (2016)

© 2016 Springer Science+Business Media New YorkIn the field of Evolutionary Computation, a common myth that ¿An Evolutionary Algorithm (EA) will outperform a local search algori... [more]

© 2016 Springer Science+Business Media New YorkIn the field of Evolutionary Computation, a common myth that ¿An Evolutionary Algorithm (EA) will outperform a local search algorithm, given enough runtime and a large-enough population¿ exists. We believe that this is not necessarily true and challenge the statement with several simple considerations. We then investigate the population size parameter of EAs, as this is the element in the above claim that can be controlled. We conduct a related work study, which substantiates the assumption that there should be an optimal setting for the population size at which a specific EA would perform best on a given problem instance and computational budget. Subsequently, we carry out a large-scale experimental study on 68 instances of the Traveling Salesman Problem with static population sizes that are powers of two between (Formula presented.) and (Formula presented.) EAs as well as with adaptive population sizes. We find that analyzing the performance of the different setups over runtime supports our point of view and the existence of optimal finite population size settings.

DOI 10.1007/s10898-016-0417-5
2016 Lo SL, Chiong R, Cornforth D, 'Ranking of high-value social audiences on Twitter', Decision Support Systems, 85 34-48 (2016)

© 2016 Elsevier B.V. All rights reserved.Even though social media offers plenty of business opportunities, for a company to identify the right audience from the massive amount of... [more]

© 2016 Elsevier B.V. All rights reserved.Even though social media offers plenty of business opportunities, for a company to identify the right audience from the massive amount of social media data is highly challenging given finite resources and marketing budgets. In this paper, we present a ranking mechanism that is capable of identifying the top-k social audience members on Twitter based on an index. Data from three different Twitter business account owners were used in our experiments to validate this ranking mechanism. The results show that the index developed using a combination of semi-supervised and supervised learning methods is indeed generic enough to retrieve relevant audience members from the three different data sets. This approach of combining Fuzzy Match, Twitter Latent Dirichlet Allocation and Support Vector Machine Ensemble is able to leverage on the content of account owners to construct seed words and training data sets with minimal annotation efforts. We conclude that this ranking mechanism has the potential to be adopted in real-world applications for differentiating prospective customers from the general audience and enabling market segmentation for better business decision making.

DOI 10.1016/j.dss.2016.02.010
Co-authors David Cornforth
2016 Lo SL, Cambria E, Chiong R, Cornforth D, 'A multilingual semi-supervised approach in deriving Singlish sentic patterns for polarity detection', Knowledge-Based Systems, 105 236-247 (2016)

© 2016 Elsevier B.V. All rights reserved.Due to the huge volume and linguistic variation of data shared online, accurate detection of the sentiment of a message (polarity detecti... [more]

© 2016 Elsevier B.V. All rights reserved.Due to the huge volume and linguistic variation of data shared online, accurate detection of the sentiment of a message (polarity detection) can no longer rely on human assessors or through simple lexicon keyword matching. This paper presents a semi-supervised approach in constructing essential toolkits for analysing the polarity of a localised scarce-resource language, Singlish (Singaporean English). Corpus-based bootstrapping using a multilingual, multifaceted lexicon was applied to construct an annotated testing dataset, while unsupervised methods such as lexicon polarity detection, frequent item extraction through association rules and latent semantic analysis were used to identify the polarity of Singlish n-grams before human assessment was done to isolate misleading terms and remove concept ambiguity. The findings suggest that this multilingual approach outshines polarity analysis using only the English language. In addition, a hybrid combination of the Support Vector Machine and a proposed Singlish Polarity Detection algorithm, which incorporates unigram and n-gram Singlish sentic patterns with other multilingual polarity sentic patterns such as negation and adversative, is able to outperform other approaches in comparison. The promising results of a pooled testing dataset generated from the vast amount of unannotated Singlish data clearly show that our multilingual Singlish sentic pattern approach has the potential to be adopted in real-world polarity detection.

DOI 10.1016/j.knosys.2016.04.024
Co-authors David Cornforth
2016 Zhang R, Chiong R, 'Solving the energy-efficient job shop scheduling problem: A multi-objective genetic algorithm with enhanced local search for minimizing the total weighted tardiness and total energy consumption', Journal of Cleaner Production, 112 3361-3375 (2016)

© 2015 Elsevier Ltd. All rights reserved.In recent years, there has been a growing concern over the environmental impact of traditional manufacturing, especially in terms of ener... [more]

© 2015 Elsevier Ltd. All rights reserved.In recent years, there has been a growing concern over the environmental impact of traditional manufacturing, especially in terms of energy consumption and related emissions of carbon dioxide. Besides the adoption of new equipment, production scheduling could play a key role in reducing the total energy consumption of a manufacturing plant. In this paper, we explicitly introduce the objective of minimizing energy consumption into a typical production scheduling model, i.e., the job shop scheduling problem, based on a machine speed scaling framework. To solve this bi-objective optimization problem, we propose a multi-objective genetic algorithm incorporated with two problem-specific local improvement strategies. These local improvement procedures aim to enhance the solution quality by utilizing the mathematical models of two restricted subproblems derived from the original problem. Comprehensive computational experiments have been carried out to verify the effectiveness of the proposed solution approach. The results presented in this work may be useful for future research on energy-efficient production scheduling.

DOI 10.1016/j.jclepro.2015.09.097
2015 Zhang R, Chiong R, Michalewicz Z, Chang P-C, 'Sustainable Scheduling of Manufacturing and Transportation Systems', European Journal of Operational Research, 248 741-743 (2015) [C3]
DOI 10.1016/j.ejor.2015.09.019
2015 Xiong T, Bao Y, Hu Z, Chiong R, 'Forecasting interval time series using a fully complex-valued RBF neural network with DPSO and PSO algorithms', Information Sciences, 305 77-92 (2015) [C1]

© 2015 Elsevier Inc.Interval time series prediction is one of the most challenging research topics in the field of time series modeling and prediction. In view of the remarkable ... [more]

© 2015 Elsevier Inc.Interval time series prediction is one of the most challenging research topics in the field of time series modeling and prediction. In view of the remarkable function approximation capability of fully complex-valued radial basis function neural networks (FCRBFNNs), we set out to investigate the possibility of forecasting interval time series by denoting the lower and upper bounds of the interval as real and imaginary parts of a complex number, respectively. This results in a complex-valued interval. We then model the resulted complex-valued interval time series via a FCRBFNN. Furthermore, we propose to evolve the FCRBFNN by using particle swarm optimization (PSO) and discrete PSO for joint optimization of the structure and parameters. Finally, the proposed interval time series prediction approach is tested with simulated interval time series data as well as real interval stock price time series data from the New York Stock Exchange. Our experimental results indicate that it is a promising alternative for interval time series forecasting.

DOI 10.1016/j.ins.2015.01.029
Citations Scopus - 10Web of Science - 1
2015 Hu Z, Bao Y, Xiong T, Chiong R, 'Hybrid filter-wrapper feature selection for short-term load forecasting', Engineering Applications of Artificial Intelligence, 40 17-27 (2015) [C1]

© 2014 Elsevier Ltd.Selection of input features plays an important role in developing models for short-term load forecasting (STLF). Previous studies along this line of research ... [more]

© 2014 Elsevier Ltd.Selection of input features plays an important role in developing models for short-term load forecasting (STLF). Previous studies along this line of research have focused pre-dominantly on filter and wrapper methods. Given the potential value of a hybrid selection scheme that includes both filter and wrapper methods in constructing an appropriate pool of features, coupled with the general lack of success in employing filter or wrapper methods individually, in this study we propose a hybrid filter-wrapper approach for STLF feature selection. This proposed approach, which is believed to have taken full advantage of the strengths of both filter and wrapper methods, first uses the Partial Mutual Information based filter method to filter out most of the irrelevant and redundant features, and subsequently applies a wrapper method, implemented via a firefly algorithm, to further reduce the redundant features without degrading the forecasting accuracy. The well-established support vector regression is selected as the modeler to implement the proposed hybrid feature selection scheme. Real-world electricity load datasets from a North-American electric utility and the Global Energy Forecasting Competition 2012 have been used to test the performance of the proposed approach, and the experimental results show its superiority over selected counterparts.

DOI 10.1016/j.engappai.2014.12.014
Citations Scopus - 14Web of Science - 4
2015 Ding JY, Song S, Gupta JND, Zhang R, Chiong R, Wu C, 'An improved iterated greedy algorithm with a Tabu-based reconstruction strategy for the no-wait flowshop scheduling problem', Applied Soft Computing Journal, 30 604-613 (2015) [C1]

© 2015 Elsevier B.V. All rights reserved.This paper proposes a Tabu-mechanism improved iterated greedy (TMIIG) algorithm to solve the no-wait flowshop scheduling problem with a m... [more]

© 2015 Elsevier B.V. All rights reserved.This paper proposes a Tabu-mechanism improved iterated greedy (TMIIG) algorithm to solve the no-wait flowshop scheduling problem with a makespan criterion. The idea of seeking further improvement in the iterated greedy (IG) algorithm framework is based on the observation that the construction phase of the original IG algorithm may not achieve good performance in escaping from local minima when incorporating the insertion neighborhood search. To overcome this limitation, we have modified the IG algorithm by utilizing a Tabu-based reconstruction strategy to enhance its exploration ability. A powerful neighborhood search method that involves insert, swap, and double-insert moves is then applied to obtain better solutions from the reconstructed solution in the previous step. Empirical results on several benchmark problem instances and those generated randomly confirm the advantages of utilizing the new reconstruction scheme. In addition, our results also show that the proposed TMIIG algorithm is relatively more effective in minimizing the makespan than other existing well-performing heuristic algorithms.

DOI 10.1016/j.asoc.2015.02.006
Citations Scopus - 4
2015 Hu Z, Bao Y, Chiong R, Xiong T, 'Mid-term interval load forecasting using multi-output support vector regression with a memetic algorithm for feature selection', Energy, 84 419-431 (2015) [C1]

© 2015 Elsevier Ltd.Accurate forecasting of mid-term electricity load is an important issue for power system planning and operation. Instead of point load forecasting, this study... [more]

© 2015 Elsevier Ltd.Accurate forecasting of mid-term electricity load is an important issue for power system planning and operation. Instead of point load forecasting, this study aims to model and forecast mid-term interval loads up to one month in the form of interval-valued series consisting of both peak and valley points by using MSVR (Multi-output Support Vector Regression). In addition, an MA (Memetic Algorithm) based on the firefly algorithm is used to select proper input features among the feature candidates, which include time lagged loads as well as temperatures. The capability of this proposed interval load modeling and forecasting framework to predict daily interval electricity demands is tested through simulation experiments using real-world data from North America and Australia. Quantitative and comprehensive assessments are performed and the experimental results show that the proposed MSVR-MA forecasting framework may be a promising alternative for interval load forecasting.

DOI 10.1016/j.energy.2015.03.054
Citations Scopus - 5
2015 Chiong R, Kirley M, 'Promotion of cooperation in social dilemma games via generalised indirect reciprocity', Connection Science, 27 417-433 (2015) [C1]

© 2015 Taylor & Francis.This paper presents a novel generalised indirect reciprocity approach for promoting cooperation in social dilemma games. Here, players decide upon an acti... [more]

© 2015 Taylor & Francis.This paper presents a novel generalised indirect reciprocity approach for promoting cooperation in social dilemma games. Here, players decide upon an action to play in the game based on public information (or ¿external cues¿) rather than individual-specific information. The public information is constantly updated according to the underlying learning model. Comprehensive simulation experiments using the N-player Prisoner's Dilemma (PD) and Snowdrift (SD) games show that generalised indirect reciprocity promotes high levels of cooperation across a wide range of conditions. This is despite the fact that the make-up of player groups is continually changing. As expected, the extent of cooperative behaviour observed in the ¿constraint-relaxed¿ N-player SD game is significantly higher than the N-player PD game. Our proposed generalised indirect reciprocity model may shed light on the conundrum of cooperation between anonymous individuals.

DOI 10.1080/09540091.2015.1080226
2015 Tian X, Chiong RJW, Martin B, Stockdale R, 'Editor. Special issue of the Journal of Systems and Information Technology on Business Intelligence', Journal of Systems and Information Technology on Business Intelligence, 17 (2015) [C6]
DOI 10.1108/JSIT-04-2015-0032
2015 Tian X, Chiong R, Martin B, Stockdale R, 'Introduction to the special issue of the Journal of Systems and Information Technology on business intelligence', Journal of Systems and Information Technology, 17 (2015) [C3]
DOI 10.1108/JSIT-04-2015-0032
2015 Lo SL, Chiong R, Cornforth D, 'Using Support Vector Machine Ensembles for Target Audience Classification on Twitter', PLOS ONE, 10 (2015) [C1]
DOI 10.1371/journal.pone.0122855
Citations Scopus - 4
Co-authors David Cornforth
2015 Li B, Chiong R, Lin M, 'A balance-evolution artificial bee colony algorithm for protein structure optimization based on a three-dimensional AB off-lattice model', Computational Biology and Chemistry, 54 1-12 (2015) [C1]

© 2014 Elsevier Ltd. All rights reserved.Protein structure prediction is a fundamental issue in the field of computational molecular biology. In this paper, the AB off-lattice mo... [more]

© 2014 Elsevier Ltd. All rights reserved.Protein structure prediction is a fundamental issue in the field of computational molecular biology. In this paper, the AB off-lattice model is adopted to transform the original protein structure prediction scheme into a numerical optimization problem. We present a balance-evolution artificial bee colony (BE-ABC) algorithm to address the problem, with the aim of finding the structure for a given protein sequence with the minimal free-energy value. This is achieved through the use of convergence information during the optimization process to adaptively manipulate the search intensity. Besides that, an overall degradation procedure is introduced as part of the BE-ABC algorithm to prevent premature convergence. Comprehensive simulation experiments based on the well-known artificial Fibonacci sequence set and several real sequences from the database of Protein Data Bank have been carried out to compare the performance of BE-ABC against other algorithms. Our numerical results show that the BE-ABC algorithm is able to outperform many state-of-the-art approaches and can be effectively employed for protein structure optimization.

DOI 10.1016/j.compbiolchem.2014.11.004
Citations Scopus - 6Web of Science - 1
2015 Weise T, Chiong R, 'An alternative way of presenting statistical test results when evaluating the performance of stochastic approaches', Neurocomputing, 147 235-238 (2015) [C1]

© 2014 Elsevier B.V.Stochastic approaches such as evolutionary algorithms have been widely used in various science and engineering problems. When comparing the performance of a s... [more]

© 2014 Elsevier B.V.Stochastic approaches such as evolutionary algorithms have been widely used in various science and engineering problems. When comparing the performance of a set of stochastic algorithms, it is necessary to statistically evaluate which algorithms are the most suitable for solving a given problem. The outcome of statistical tests comparing N=2 processes, where N is the number of algorithms, is often presented in tables. This can become confusing for larger numbers of N. Such a scenario is, however, very common in both numerical and combinatorial optimization as well as in the domain of stochastic algorithms in general. In this letter, we introduce an alternative way of visually presenting the results of statistical tests for multiple processes in a compact and easy-to-read manner using a directed acyclic graph (DAG), in the form of a simplified Hasse diagram. The rationale of doing so is based on the fact that the outcome of the tests is always at least a strict partial order, which can be appropriately presented via a DAG. The goal of this brief communication is to promote the use of this approach as a means for presenting the results of comparisons between different optimization methods.

DOI 10.1016/j.neucom.2014.06.071
Citations Scopus - 2Web of Science - 2
2015 Boyton J, Ayscough P, Kaveri D, Chiong R, 'Suboptimal business intelligence implementations: Understanding and addressing the problems', Journal of Systems and Information Technology, 17 307-320 (2015) [C1]
DOI 10.1108/JSIT-03-2015-0023
2015 Harrison R, Parker A, Alexander G, Chiong R, Tian X, 'The role of technology in the management and exploitation of internal business intelligence', Journal of Systems and Information Technology, 17 247-262 (2015) [C1]
DOI 10.1108/JSIT-04-2015-0030
2014 Catay B, Chiong R, Cordón O, Siarry P, 'Computational intelligence in production and logistics systems: Solving vehicle routing, supply chain network, and air-traffic trajectory planning problems [guest editorial]', IEEE Computational Intelligence Magazine, 9 16-17 (2014) [C3]
DOI 10.1109/MCI.2014.2350932
2014 Weise T, Chiong R, Lassig J, Tang K, Tsutsui S, Chen W, et al., 'Benchmarking optimization algorithms: An open source framework for the traveling salesman problem', IEEE Computational Intelligence Magazine, 9 40-52 (2014) [C1]
DOI 10.1109/MCI.2014.2326101
Citations Scopus - 12Web of Science - 3
2014 Alshibly H, Chiong R, 'Customer empowerment: Does it influence electronic government success? A citizen-centric perspective', Electronic Commerce Research and Applications, (2014) [C1]

© 2015 Elsevier B.V. Electronic government (or e-government) initiatives are widespread across the globe. The increasing interest in e-government raises the issue of how governme... [more]

© 2015 Elsevier B.V. Electronic government (or e-government) initiatives are widespread across the globe. The increasing interest in e-government raises the issue of how governments can increase citizen adoption and usage of their online services. In this study, the fundamental argument is that citizens can be viewed as customers, and that e-government success can be measured by the extent to which customer net benefits are positively influenced. Hence, the key consequents of e-government success are customer-related, and the antecedents of such success have to be considered from the customer viewpoint. We advocate that government agencies must consider their customers' perceptions of empowerment as a key causal mechanism in deriving value from e-government systems. However, the literature appears to lack this perspective. This study aims to fill the gap by proposing a theoretical model and an associated evaluation tool that measures the e-government performance from a customer empowerment perspective. The model was validated by a survey method and analyzed using partial least squares. The results support our argument and show that all paths in the proposed model are significant.

DOI 10.1016/j.elerap.2015.05.003
Citations Scopus - 1
2013 Chiong R, Weise T, Michalewicz Z, 'Preface', Variants of Evolutionary Algorithms for Real-World Applications, V-X (2013)
DOI 10.1007/978-3-642-23424-8
2013 Catay B, Chiong R, Siarry P, 'Computational intelligence in production and logistics systems', International Journal Production Economics, 145 1-3 (2013) [C3]
Citations Scopus - 4Web of Science - 1
2013 Abedini M, Kirley M, Chiong R, 'Incorporating feature ranking and evolutionary methods for the classification of high-dimensional DNA microarray gene expression data', Australasian Medical Journal, 6 272-279 (2013) [C1]

Background: DNA microarray gene expression classification poses a challenging task to the machine learning domain. Typically, the dimensionality of gene expression data sets could... [more]

Background: DNA microarray gene expression classification poses a challenging task to the machine learning domain. Typically, the dimensionality of gene expression data sets could go from several thousands to over 10,000 genes. A potential solution to this issue is using feature selection to reduce the dimensionality. Aim The aim of this paper is to investigate how we can use feature quality information to improve the precision of microarray gene expression classification tasks. Method: We propose two evolutionary machine learning models based on the eXtended Classifier System (XCS) and a typical feature selection methodology. The first one, which we call FS-XCS, uses feature selection for feature reduction purposes. The second model is GRD-XCS, which uses feature ranking to bias the rule discovery process of XCS. Results: The results indicate that the use of feature selection/ranking methods is essential for tackling high-dimensional classification tasks, such as microarray gene expression classification. However, the results also suggest that using feature ranking to bias the rule discovery process performs significantly better than using the feature reduction method. In other words, using feature quality information to develop a smarter learning procedure is more efficient than reducing the feature set. Conclusion: Our findings have shown that extracting feature quality information can assist the learning process and improve classification accuracy. On the other hand, relying exclusively on the feature quality information might potentially decrease the classification performance (e.g., using feature reduction). Therefore, we recommend a hybrid approach that uses feature quality information to direct the learning process by highlighting the more informative features, but at the same time not restricting the learning process to explore other features.

DOI 10.4066/AMJ.2013.1641
Citations Scopus - 2
2012 Chiong R, Kirley M, 'Random Mobility and the Evolution of Cooperation in Spatial N-player Iterated Prisoner's Dilemma Games', Physica A: Statistical Mechanics and its Applications, 391 3915-3923 (2012) [C1]
DOI 10.1016/j.physa.2012.03.010
Citations Scopus - 8Web of Science - 4
2012 Chiong R, Siarry P, 'Local search for real-world scheduling and planning', ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 25 207-208 (2012) [C3]
DOI 10.1016/j.engappai.2011.07.008
Citations Scopus - 2Web of Science - 1
2012 Tang K, Weise T, Chiong R, 'Evolutionary Optimization: Pitfalls and Booby Traps', Journal of Computer Science and Technology, 27 907-936 (2012) [C1]
DOI 10.1007/s11390-012-1274-4
Citations Scopus - 22Web of Science - 16
2012 Chiong R, Kirley M, 'Effects of Iterated Interactions in Multi-player Spatial Evolutionary Games', IEEE Transactions on Evolutionary Computation, 16 537-555 (2012) [C1]
DOI 10.1109/TEVC.2011.2167682
Citations Scopus - 15Web of Science - 7
2012 Chiong R, Jovanovic J, 'Collaborative Learning in Online Study Groups: An Evolutionary Game Theory Perspective', Journal of Information Technology Education, 11 81-101 (2012) [C1]
Citations Scopus - 10
2012 Jovanovic J, Weise T, Chiong R, 'Social networking, teaching, and learning', Interdisciplinary Journal of Information, Knowledge, and Management, 7 39-43 (2012) [C3]
Citations Scopus - 1
2012 Jovanovic J, Chiong R, 'Introduction to the special section on game-based learning: Design and applications', Interdisciplinary Journal of Information, Knowledge, and Management, 7 201-203 (2012) [C3]
2011 Chiong R, Weise T, 'Special issue on modern search heuristics and applications', Evolutionary Intelligence, 4 1-2 (2011) [C3]
DOI 10.1007/s12065-011-0050-7
Citations Scopus - 3
2011 Pu W, Weise T, Chiong R, 'Novel Evolutionary Algorithms for Supervised Classification Problems: An Experimental Study', Evolutionary Intelligence, 4 3-16 (2011) [C1]
DOI 10.1007/s12065-010-0047-7
Citations Scopus - 10
2011 Weise T, Chiong R, 'A Novel Extremal Optimization Approach for the Template Design Problem', International Journal of Organizational and Collective Intelligence, 2 1-16 (2011) [C1]
DOI 10.4018/joci.2011040101
2011 Su SI, Chiong R, 'Adaptive business intelligence for information and communication technology management', Journal of Information, Intelligence and Knowledge, 1 375-390 (2011)
2010 Moser I, Chiong R, 'Dynamic function optimisation with hybridised extremal dynamics', Memetic Computing, 2 137-148 (2010) [C1]

Dynamic function optimisation is an important research area because many real-world problems are inherently dynamic in nature. Over the years, a wide variety of algorithms have be... [more]

Dynamic function optimisation is an important research area because many real-world problems are inherently dynamic in nature. Over the years, a wide variety of algorithms have been proposed to solve dynamic optimisation problems, and many of these algorithms have used the Moving Peaks (MP) benchmark to test their own capabilities against other approaches. This paper presents a detailed account of our hybridised Extremal Optimisation (EO) approach that has achieved hitherto unsurpassed results on the three standardised scenarios of the MP problem. Several different components are used in the hybrid EO, and it has been shown that a large proportion of the quality of its outstanding performance is due to the local search component. In this paper, the behaviour of the local search algorithms used is analysed, and the roles of other components are discussed. In the concluding remarks, the generalisation ability of this method and its wider applicability are highlighted. © Springer-Verlag 2009.

DOI 10.1007/s12293-009-0027-6
Citations Scopus - 12
2010 Chiong R, 'Programming with games', IEEE Learning Technology, 12 14-16 (2010)
2010 Chiong R, 'Preface', Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, XV-XX (2010)
DOI 10.4018/978-1-60566-705-8
2009 Chiong R, Weise T, 'Global optimisation and mobile learning', IEEE Learning Technology, 11 26-28 (2009)
2008 Chiong R, 'A hybrid learning for named entity recognition systems', INFOCOMP Journal of Computer Science, 7 92-98 (2008)
2008 Chiong R, Jankovic L, 'Learning game strategy design through iterated Prisoner's Dilemma', International Journal of Computer Applications in Technology, 32 216-223 (2008) [C1]

The article investigates games strategies on the basis of experiments with iterated Prisoner's Dilemma, a classical non-zero sum game. The objective is to determine which strategi... [more]

The article investigates games strategies on the basis of experiments with iterated Prisoner's Dilemma, a classical non-zero sum game. The objective is to determine which strategies have the best chance of winning. Although some strategies, like tit-for-tat, emerge as better than others in some cases, it appears that there is no overall winning strategy, but that success or failure of individual strategies depends upon the strategies adopted by a population of opponents. Therefore, the winning strategy will change dynamically, and will need to be determined while the game in progress. Based on the results of this work, a strategy engine for games development is proposed, and a future development of strategy middleware is discussed. Copyright © 2008 Inderscience Enterprises Ltd.

DOI 10.1504/IJCAT.2008.020957
2007 Chiong R, Ooi KB, 'A comparison between genetic algorithms and evolutionary programming based on the cutting stock problem', Engineering Letters, 14 72-77 (2007)
Show 39 more journal articles

Conference (55 outputs)

Year Citation Altmetrics Link
2016 Hu Z, Chiong R, Pranata I, Susilo W, Bao Y, 'Identifying Malicious Web Domains Using Machine Learning Techniques with Online Credibility and Performance Data, 2016 International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada' (2016)
Co-authors Ilung Pranata
2016 Müller MB, Adam MTP, Cornforth DJ, Chiong R, Krämer J, Weinhardt C, 'Selecting physiological features for predicting bidding behavior in electronic auctions', Proceedings of the Forty-Ninth Annual Hawaii International Conference on System Sciences (HICSS) (2016)
DOI 10.1109/HICSS.2016.55
Co-authors David Cornforth, Marc Adam
2015 Liu W, Weise T, Wu Y, Chiong R, 'Hybrid ejection chain methods for the traveling salesman problem', Communications in Computer and Information Science (2015) [E1]

© Springer-Verlag Berlin Heidelberg 2015.Local search such as Ejection Chain Methods (ECMs) based on the stem-and-cycle (S&C) reference structure, Lin-Kernighan (LK) heuristics, ... [more]

© Springer-Verlag Berlin Heidelberg 2015.Local search such as Ejection Chain Methods (ECMs) based on the stem-and-cycle (S&C) reference structure, Lin-Kernighan (LK) heuristics, as well as the recently proposed Multi-Neighborhood Search (MNS), are among the most competitive algorithms for the Traveling Salesman Problem (TSP). In this paper, we carry out a large-scale experiment with all 110 symmetric instances from the TSPLib to investigate the performances of these algorithms. Our study is different from previous work along this line of research in that we consider the entire runtime behavior of the algorithms, not just their end results. This leads to one of the most comprehensive comparisons of these algorithms to date. We introduce a new, improved S&C-ECM that can outperform LK and MNS. We then develop new hybrid versions of our ECM implementations by combining them with Evolutionary Algorithms and Population-based Ant Colony Optimization (PACO). We compare them to similar hybrids of LK and MNS. Our results show that hybrid PACO-S&C, PACO-LK and PACO-MNS are all very efficient. We also find that the full runtime behavior comparison provides deeper and clearer insights, while focusing on end results only would have led to a misleading conclusion.

DOI 10.1007/978-3-662-49014-3_25
2015 Lo SL, Cornforth D, Chiong R, 'Use of a High-Value Social Audience index for target audience identification on Twitter', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2015) [E1]

© Springer International Publishing Switzerland 2015.With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. Th... [more]

© Springer International Publishing Switzerland 2015.With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according to available resources, so that a high-value social audience can potentially be transformed to customers, and hence improve the return on investment.

Co-authors David Cornforth
2015 Xu D, Weise T, Wu Y, Lässig J, Chiong R, 'An investigation of hybrid Tabu search for the traveling salesman problem', Bio-Inspired Computing - Theories and Applications (2015) [E1]
DOI 10.1007/978-3-662-49014-3_47
2015 Lo SL, Cornforth DJ, chiong R, 'Identifying the high-value social audience from Twitter through text-mining methods', Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (2015) [E1]
DOI 10.1007/978-3-319-13359-1_26
Co-authors David Cornforth
2015 Lo SL, Cornforth DJ, Chiong R, 'Effects of training datasets on both the Extreme Learning Machine and Support Vector Machine for target Audience Identification on Twitter', Proceedings of ELM-2014 Volume 1 (2015) [E1]
DOI 10.1007/978-3-319-14063-6_35
Co-authors David Cornforth
2015 Wu Y, Weise T, Chiong R, 'Local search for the traveling salesman problem: A comparative study', Proceedings of the IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC 2015) (2015) [E1]
DOI 10.1109/ICCI-CC.2015.7259388
Citations Scopus - 2
2014 Li B, Chiong R, Gong LG, 'Search-evasion path planning for submarines using the Artificial Bee Colony algorithm', Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014 (2014) [E1]

© 2014 IEEE.Submarine search-evasion path planning aims to acquire an evading route for a submarine so as to avoid the detection of hostile anti-submarine searchers such as helic... [more]

© 2014 IEEE.Submarine search-evasion path planning aims to acquire an evading route for a submarine so as to avoid the detection of hostile anti-submarine searchers such as helicopters, aircraft and surface ships. In this paper, we propose a numerical optimization model of search-evasion path planning for invading submarines. We use the Artificial Bee Colony (ABC) algorithm, which has been confirmed to be competitive compared to many other nature-inspired algorithms, to solve this numerical optimization problem. In this work, several search-evasion cases in the two-dimensional plane have been carefully studied, in which the anti-submarine vehicles are equipped with sensors with circular footprints that allow them to detect invading submarines within certain radii. An invading submarine is assumed to be able to acquire the real-time locations of all the anti-submarine searchers in the combat field. Our simulation results show the efficacy of our proposed dynamic route optimization model for the submarine search-evasion path planning mission.

DOI 10.1109/CEC.2014.6900224
Citations Scopus - 5Web of Science - 2
2014 Alharbi N, Athauda R, Chiong R, 'A Survey of CSCL Script Tools that Support Designing Collaborative Scenarios', 2014 International Conference on Web and Open Access to Learning Conference (2014) [E1]
DOI 10.1109/ICWOAL.2014.7009226
Co-authors Rukshan Athauda
2014 Li B, Chiong R, Lin M, 'A two-layer optimization framework for UAV path planning with interval uncertainties', IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIPLS 2014: 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems, Proceedings (2014) [E1]
DOI 10.1109/CIPLS.2014.7007170
2014 Jiang Y, Weise T, Lassig J, Chiong R, Athauda R, 'Comparing a hybrid branch and bound algorithm with evolutionary computation methods, local search and their hybrids on the TSP', IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIPLS 2014: 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems, Proceedings (2014) [E1]
DOI 10.1109/CIPLS.2014.7007174
Co-authors Rukshan Athauda
2014 Alharbi N, Athauda R, Chiong R, 'An Integrated Framework for Collaboration in Online Learning Using CSCL Scripts', The 9th International Conference on Information Technology and Application (ICITA 2014) (2014) [E1]
Co-authors Rukshan Athauda
2014 Li X, Tian X, Chiong RJW, 'Provenancing qualifications in higher education: An Australian-Chinese case study', Proceedings of Informing Science & IT Education Conference (InSITE 2014) (2014) [E1]
2013 Abedini M, Kirley M, Chiong R, Weise T, 'GPU-accelerated eXtended Classifier System', 2013 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING (CIDM) (2013) [E1]
2013 Ouyang J, Weise T, Devert A, Chiong RJW, 'SDGP: A Developmental Approach for Traveling Salesman Problems', Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS) (2013) [E1]
DOI 10.1109/CIPLS.2013.6595203
2013 Chiong RJW, Kirley M, 'A multi-agent based migration model for evolving cooperation in the spatial N-player Snowdrift game', Prima 2013 Principles and Practice of Multi-Agent Systems 16th International Conference Proceedings (2013) [E1]
DOI 10.1007/978-3-642-44927-7
2012 Chiong R, Kirley M, 'The evolution of cooperation via stigmergic interactions', Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2012) (2012) [E1]
2012 Abedini M, Kirley M, Chiong R, 'FS-XCS vs. GRD-XCS: An Analysis Using High-dimensional DNA Microarray Gene Expression Data Sets', Proceedings of the 2nd Australian Workshop on Artificial Intelligence in Health (AIH 2012) (2012) [E1]
2011 Chiong R, Kirley M, 'Iterated N-Player games on small-world networks', Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011 (2011) [E1]
Citations Scopus - 6Web of Science - 1
2011 Weise T, Niemczyk S, Chiong R, Wan M, 'A framework for multi-model EDAs with model recombination', Proceedings of the European Conference on the Applications of Evolutionary Computation (EvoApplications 2011) (2011) [E1]
Citations Scopus - 1
2010 Chiong R, Kirley M, 'Co-evolution of agent strategies in N-player dilemmas', Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) (2010) [E1]
2010 Weise T, Chiong R, 'Evolutionary data mining approaches for rule-based and tree-based classifiers', Proceedings of the 9th IEEE International Conference on Cognitive Informatics (ICCI 2010) (2010) [E1]
Citations Scopus - 1
2010 Chiong R, Kirley M, 'Imitation vs evolution: analysing the effects of strategy update mechanisms in N-player social dilemmas', Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2010) (2010) [E1]
2010 Chiong R, Kirley M, 'Evolving cooperation in the spatial N-player snowdrift game', Proceedings of the 23rd Australasian Joint Conference on Artificial Intelligence (AI 2010) (2010) [E1]
Citations Scopus - 2Web of Science - 2
2009 Chiong R, Weise T, Lau BT, 'Template design using Extremal Optimization with multiple search operators', Proceedings of the International Conference on Soft Computing and Pattern Recognition (SoCPaR 2009) (2009) [E1]
2009 Lau BT, Thai TC, Chiong R, 'An intelligent real-time communication assistant for the disabled', Proceedings of the International Conference on Soft Computing and Pattern Recognition (SoCPaR 2009) (2009) [E1]
2009 Moser I, Chiong R, 'A hooke-jeeves based memetic algorithm for solving dynamic optimisation problems', Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2009) (2009) [E1]
Citations Scopus - 2Web of Science - 3
2009 Chiong R, Kirley M, 'Co-evolutionary learning in the N-player iterated prisoner's dilemma with a structured environment', Proceedings of the 4th Australian Conference on Artificial Life (ACAL 2009) (2009) [E1]
Citations Web of Science - 1
2009 Dhakal S, Chiong R, Lau BT, 'A comparative study of tree-based search algorithms on the London Underground', Proceedings of the 1st Malaysian Joint Conference on Artificial Intelligence (MJCAI 2009) (2009) [E1]
2009 Chiong R, Dhakal S, Lau BT, 'Solving the examination timetabling problem with controlled avalanche of changes', Proceedings of the 6th International Conference on Information Technology in Asia (CITA 2009) (2009) [E1]
2008 Chiong R, Dhakal S, 'Modelling database security through agent-based simulation', Proceedings of the 2nd Asia International Conference on Modelling and Simulation (AMS 2008) (2008) [E1]
Citations Scopus - 2
2008 Chang YY, Yung S, Chiong R, 'A novel approach for intelligent route finding through cumulative proximity evaluation', Proceedings of the 2nd Asia International Conference on Modelling and Simulation (AMS 2008) (2008) [E1]
2008 Jap WJ, Sutanto JH, Chiong R, 'An implementation of ant colony optimisation for solving cutting stock problem', Proceedings of the 4th IASTED International Conference on Advances in Computer Science and Technology (ACST 2008) (2008) [E1]
2008 Chiong R, Lau BT, 'A hybrid Naive Bayes approach for information filtering', Proceedings of the 3rd IEEE Conference on Industrial Electronics and Applications (ICIEA 2008) (2008) [E1]
Citations Scopus - 1
2008 Chiong R, Chang YY, Chai PC, Wong AL, 'A selective mutation based evolutionary programming for solving cutting stock problem without contiguity', Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2008) (2008) [E1]
Citations Scopus - 2Web of Science - 1
2008 Dhakal S, Chiong R, 'A hybrid nearest neighbour and progressive improvement approach for travelling salesman problem', Proceedings of the 3rd International Symposium on Information Technology (ITSIM 2008) (2008) [E1]
Citations Scopus - 1
2008 Chiong R, Sutanto JH, Jap WJ, 'A comparative study on informed and uninformed search for intelligent travel planning in Borneo Island', Proceedings of the 3rd International Symposium on Information Technology (ITSIM 2008) (2008) [E1]
Citations Scopus - 1Web of Science - 1
2008 Chiong R, Dhakal S, 'On the insecurity of personal firewall', Proceedings of the 3rd International Symposium on Information Technology (ITSIM 2008) (2008) [E1]
2007 Chiong R, Lee MH, Tham CM, 'The implications of Web 2.0 on the delivery of e-learning', Proceedings of the UiTM International Conference on E-Learning (UiCEL 2007) (2007) [E1]
2007 Chiong R, 'Applying Genetic Algorithms to Economy Market using Iterated Prisoner's Dilemma', APPLIED COMPUTING 2007, VOL 1 AND 2 (2007) [E1]
Citations Scopus - 4
2007 Chiong R, 'Modelling agent strategies in simulated market using iterated prisoner's dilemma', COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2007, PT 3, PROCEEDINGS (2007) [E1]
2007 Chiong R, Dhakal S, Jankovic L, 'Effects of neighbourhood structure on evolution of cooperation in N-Player Iterated Prisoner's Dilemma', INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2007 (2007) [E1]
Citations Scopus - 3Web of Science - 5
2007 Theng LB, Chiong R, 'An improved snake for automatic building extraction', CIMMACS '07: PROCEEDINGS OF THE 6TH WSEAS INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE, MAN-MACHINE SYSTEMS AND CYBERNETICS (2007) [E1]
2007 Suai W, Chiong R, 'A comparison of the security features of .NET and J2EE', Proceedings of the 2nd International Conference on Informatics (Informatics 2007) (2007) [E1]
2007 Chiong R, 'A hybrid classification approach for content-based email filtering', Proceedings of the 5th International Conference on Information Technology in Asia (CITA 2007) (2007) [E1]
2007 Su SI, Chiong R, 'Managing information and communication technology through business intelligence', Proceedings of the International Conference on Information Technology and Management (ICITM 2007) (2007) [E1]
2006 Issac B, Chiong R, Jacob SM, 'Analysis of phishing attacks and countermeasures', Managing Information in the Digital Economy: Issues & Solutions (2006) [E1]
2006 Chiong R, Wei W, 'Named entity recognition using hybrid machine learning approach', Proceedings of the Fifth IEEE International Conference on Cognitive Informatics, Vols 1 and 2 (2006) [E1]
Citations Scopus - 1
2006 Chiong R, Wong DML, Jankovic L, 'Agent-based economic modelling with iterated prisoner's dilemma', 2006 International Conference on Computing and Informatics, ICOCI '06 (2006) [E1]

This paper presents a method on modelling the economy market using agent-based representation and iterated prisoner's dilemma (IPD). While IPD has been widely used in various prob... [more]

This paper presents a method on modelling the economy market using agent-based representation and iterated prisoner's dilemma (IPD). While IPD has been widely used in various problems, there is little work done in modelling the dynamics of market behaviour and it is the main objective of this work to fill in this gap. We create a simulated market environment with agents acting as firms to perform transactions among each other with chosen IPD strategy. From the empirical results, we investigate the strategic interactions among different firms in relation to real-world transaction scenario. In the concluding remarks, we present our observation on the qualities of a winning strategy. ©2006 IEEE.

DOI 10.1109/ICOCI.2006.5276488
2006 Chiong R, Wong DM, 'Survey on the applications of artificial neural networks in computer games', Proceedings of the 3rd International Conference on Artificial Intelligence in Engineering and Technology (ICAIET 2006) (2006) [E1]
2006 Chiong R, 'An improved evolutionary approach for solving one-dimensional cutting stock problem', Proceedings of the 3rd International Conference on Artificial Intelligence in Engineering and Technology (ICAIET 2006) (2006) [E1]
2006 Chiong R, Jankovic L, 'Genetic algorithm as a game strategy in iterated prisoner's dilemma', Proceedings of the International Conference on Modeling and Simulation (MS 2006) (2006) [E1]
2006 Chiong R, Beng OK, 'A comparison between genetic algorithms and evolutionary programming based on cutting stock problem', IMECS 2006: International Multiconference of Engineers and Computer Scientists (2006) [E1]
2004 Jankovic L, Chiong R, 'Investigation of strategy dynamics using prisoner's dilemma problem (invited paper)', Proceedings of the 5th International Conference on Computer Games: Artificial Intelligence, Design and Education (CGAIDE 2004) (2004) [E1]
Show 52 more conferences
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Grants and Funding

Summary

Number of grants 9
Total funding $148,453

Click on a grant title below to expand the full details for that specific grant.


20161 grants / $112,000

Multi-Output Support Vector Regression Based Prediction Techniques$112,000

Funding body: National Natural Science Foundation of China

Funding body National Natural Science Foundation of China
Project Team

Yukun Bao

Scheme National Natural Science Foundation of China
Role Investigator
Funding Start 2016
Funding Finish 2019
GNo
Type Of Funding International - Competitive
Category 3IFA
UON N

20153 grants / $7,409

Early/Mid-Career Visiting Fellowship Grant$3,409

Funding body: University of Newcastle - Faculty of Science & IT

Funding body University of Newcastle - Faculty of Science & IT
Scheme Early/Mid-Career Visiting Fellowship Grant
Role Lead
Funding Start 2015
Funding Finish 2015
GNo
Type Of Funding Internal
Category INTE
UON N

Faculty ECA Networking/Conference Grant 2015$2,000

Funding body: University of Newcastle - Faculty of Science & IT

Funding body University of Newcastle - Faculty of Science & IT
Scheme Early Career Academic (ECA) Networking/Conference Grant
Role Lead
Funding Start 2015
Funding Finish 2015
GNo
Type Of Funding Internal
Category INTE
UON N

Faculty PVC Conference Assistance Grant 2015$2,000

Funding body: University of Newcastle - Faculty of Science & IT

Funding body University of Newcastle - Faculty of Science & IT
Scheme PVC Conference Assistance Grant
Role Lead
Funding Start 2015
Funding Finish 2015
GNo
Type Of Funding Internal
Category INTE
UON N

20143 grants / $14,044

A Framework for Next Generation Algorithm Benchmarking: Performance Testing and Community Benchmarking$10,044

Funding body: University of Newcastle - Faculty of Science & IT

Funding body University of Newcastle - Faculty of Science & IT
Project Team

Raymond Chiong

Scheme Strategic Initiative Research Fund (SIRF)
Role Lead
Funding Start 2014
Funding Finish 2014
GNo
Type Of Funding Internal
Category INTE
UON N

Faculty ECA Networking/Conference Grant 2014$2,000

Funding body: University of Newcastle - Faculty of Science & IT

Funding body University of Newcastle - Faculty of Science & IT
Project Team Doctor Raymond Chiong
Scheme Early Career Academic (ECA) Networking/Conference Grant
Role Lead
Funding Start 2014
Funding Finish 2014
GNo G1401057
Type Of Funding Internal
Category INTE
UON Y

Faculty PVC Conference Assistance Grant 2014$2,000

Funding body: University of Newcastle - Faculty of Science & IT

Funding body University of Newcastle - Faculty of Science & IT
Project Team Doctor Raymond Chiong
Scheme PVC Conference Assistance Grant
Role Lead
Funding Start 2014
Funding Finish 2014
GNo G1401185
Type Of Funding Internal
Category INTE
UON Y

20132 grants / $15,000

Intelligent Transportation Planning: Benchmarking of Novel Business Analytics Techniques using the Travelling Salesman Problem as a Test-Bed.$10,000

Funding body: University of Newcastle - Faculty of Science & IT

Funding body University of Newcastle - Faculty of Science & IT
Project Team Doctor Raymond Chiong, Associate Professor Claus Weise, Doctor Rukshan Athauda
Scheme Strategic Initiative Research Fund (SIRF)
Role Lead
Funding Start 2013
Funding Finish 2013
GNo G1401032
Type Of Funding Internal
Category INTE
UON Y

“Stigmergy, mobility and the evolution of cooperation”. $5,000

Funding body: University of Newcastle

Funding body University of Newcastle
Project Team Doctor Raymond Chiong
Scheme New Staff Grant
Role Lead
Funding Start 2013
Funding Finish 2013
GNo G1301045
Type Of Funding Internal
Category INTE
UON Y
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Research Supervision

Number of supervisions

Completed1
Current3

Total current UON EFTSL

PhD1.45

Current Supervision

Commenced Level of Study Research Title / Program / Supervisor Type
2016 PhD Human-Centred Information Systems: A Saudi Arabia Perspective
PhD (Information Systems), Faculty of Science and Information Technology, The University of Newcastle
Principal Supervisor
2014 PhD Identifying High-Value Social Entities from Twitter with Machine Learning and Multilingual Analysis.
PhD (Information Technology), Faculty of Science and Information Technology, The University of Newcastle
Principal Supervisor
2013 PhD Towards Developing Computer Supported Collaborative Learning (CSCL) Scripts to Enhance Online Learning Experiences
PhD (Information Technology), Faculty of Science and Information Technology, The University of Newcastle
Co-Supervisor

Past Supervision

Year Level of Study Research Title / Program / Supervisor Type
2015 PhD Memetic Algorithm-based Electricity Load Forecasting Models with Applications
Other Eng & Related Technologi, Huazhong University of Science And Technology
Co-Supervisor
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Research Collaborations

The map is a representation of a researchers co-authorship with collaborators across the globe. The map displays the number of publications against a country, where there is at least one co-author based in that country. Data is sourced from the University of Newcastle research publication management system (NURO) and may not fully represent the authors complete body of work.

Country Count of Publications
Australia 54
Malaysia 31
China 28
Germany 7
United Kingdom 5
More...
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Dr Raymond Chiong

Position

Senior Lecturer
School of Design Communication and IT
Faculty of Science and Information Technology

Focus area

Information Technology

Contact Details

Email raymond.chiong@newcastle.edu.au
Phone (02) 4921 7367
Fax (02) 4921 5896
Link Research Networks

Office

Room MCG15
Building McMullin Building
Location Callaghan
University Drive
Callaghan, NSW 2308
Australia
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