Dr Marcella Papini

This work proposes a bi-objective mathematical optimization model and a two-stage heuristic for a real-world application of the heterogeneous Dynamic Dial-a-Ride Problem with no rejects, i.e., a patient transportation system. The problem consists of calculating route plans to meet a set of transportation requests by using a given heterogeneous vehicle fleet. These transportation requests can be either static or dynamic, and all of them must be attended to. In the first stage of the proposed heuristic, the problem¿s static part is solved by applying a General Variable neighborhood Search based algorithm. In the second stage, the dynamic requests are dealt with by implementing a simple insertion heuristic. We create different instances based on the real data provided by a Brazilian city¿s public health care system and test the proposed approach on them. The analysis of the results shows that the higher the level of dynamism, i.e., the number of urgent requests on each instance, the smaller the objective function value will be in the static part. The results also demonstrate that a higher level of dynamism increases the chance of a time window violation happening. Besides, we use the weighted sum method of the two conflicting objectives to analyze the trade-off between them and create an approximation for the Pareto frontier.

Repositioning empty container and leasing container from leasing company are mainly the outcomes of imbalance in trade flows. How to make decision on repositioning or leasing remains a challenge in running shipping service efficiently and economically. To address such challenge, this study aims to derive guide leasing prices. If the realistic leasing price is lower than the guide price, shipping companies should consider leasing containers from leasing company; otherwise repositioning empty container is a more economical option. Both time-varying short-term and long-term guide leasing prices are determined in a shipping network with consideration of empty container devanning and laden container transportation. A two-stage approach is applied to model development. At the first stage, an empty container repositioning model is proposed with consideration of holding, transportation and lifting-on/off costs. Then, inverse optimization technique is applied to deriving the second model in order to determine the guide leasing prices. A realistic shipping network is adopted to compare long-term guide leasing prices among different ports and short-term guide leasing prices on different paths between a pair of ports. The results show that short-term guide leasing prices at a deficit port vary on different paths and they are correlated to the schedule of vessels.

This article introduces a¿solution approach for the Stochastic Capacitated Vehicle Routing Problem (SCVRP) with uncertain demands, called Robust Simulation-Based¿(RoSi) approach. RoSi aims at designing route plans that can be more or less robust based on a¿decision-maker¿weight, i.e. solutions that resist demand changes with marginal additional (recourse) cost. For that, RoSi combines simulation with heuristics. It transforms a¿complex SCVRP into a¿set of deterministic ones, where well-known¿heuristics can be applied, computing a¿set of feasible solutions. These solutions are assessed by Monte Carlo simulation, and the one that deals better with demand fluctuation is selected as the final solution. The efficiency of RoSi is compared with those of three methods in the literature: Integer Linear Programming (ILP) model, Stochastic Programming with Recourse (SPR) model, and Robust Bi-Objective¿(RoBi) approach through numerical experiments. The results show that RoSi outperforms these methods in most scenarios.

The management of university libraries faces major challenges in evaluating its performance since in many cases this assessment is performed inappropriately. One of the challenges is the lack of fair approaches to reallocate resources in university library systems. In this context, data envelopment analysis (DEA), a flexible technique that allows the use of multiple inputs and outputs to assess the performance of productive units, may prove useful. In DEA, in addition to the so-called classic models, there are the zero-sum gains (ZSG) models that, when used together, assist in resource allocation. This work aims to develop a powerful approach to help the manager to assess the performance of libraries as well as allow the reallocation of resources within an integrated library system of a university in Brazil. This two-step approach is based on the classic CCR model in the first stage and the ZSG CCR DEA (zero-sum gains data envelopment analysis CCR) model on the next stage, both oriented to inputs. The results show increases in the efficiency of libraries through the redistribution of resources. This approach is invaluable to the management of library systems since it provides an instrument for improving resource utilization.

The dynamic and stochastic vehicle routing problem (DSVRP) can be modelled as a stochastic program (SP). In a two-stage SP with recourse model, the first stage minimizes the a priori routing plan cost and the second stage minimizes the cost of corrective actions, performed to deal with changes in the inputs. To deal with the problem, approaches based either on stochastic modelling or on sampling can be applied. Sampling-based methods incorporate stochastic knowledge by generating scenarios set on realizations drawn from distributions. In this paper we proposed a robust solution approach for the capacitated DSVRP based on sampling strategies. We formulated the problem as a two-stage stochastic program model with recourse. In the first stage the a priori routing plan cost is minimized, whereas in the second stage the average of higher moments for the recourse cost calculated via a set of scenarios is minimized. The idea is to include higher moments in the second stage aiming to compute a robust a priori routing plan that minimizes transportation costs while permitting small changes in the demands without changing solution structure. Additionally, the approach allows managers to choose between optimality and robustness, that is, transportation costs and reconfiguration. The computational results on a generic dynamic benchmark dataset show that the robust routing plan can cover unmet demand while incurring little extra costs as compared to the preplanning. We observed that the plan of routes is more robust; that is, not only the expected real cost, but also the increment within the planned cost is lower.

Employment of Electric Commercial Vehicles (ECVs) constitutes measures to achieve sustainable Urban Freight Transport (UFT). Despite a critical need for ECVs, in industry, the market penetration of ECVs in UFT has remained relatively low. To increase such market penetration, one crucial issue to consider is to obtain a satisfactory match between characteristics of ECVs and requirements of UFT. However, matching diverse types of ECVs and various delivery tasks in UFT leads to many possibilities. The present paper refers to such possibilities as diversity and denotes them as ECV-UFT combinations. Potentials inherent in this diversity seem ignored by the majority of the literature. Therefore, the present paper explores the significance of studying such diversity for the market penetration. In particular, the paper identifies the primary areas of focus and the extent of the diversity already considered in the literature. To accomplish this identification, a Systematic Literature Review (SLR) is applied. The SLR follows a sequence of activities, including selecting sources and keywords, as well as classifying and summarizing results. Findings unveil that the literature has primarily focused on issues concerning the feasibility of ECVs, the adaptation of logistics and vehicle concepts, and support of stakeholders. Furthermore, little consideration of the diversity in the employment of ECVs in UFT is observed as a consequence accounting for the low market penetration. Finally, building on the diversity to increase market penetration, the paper proposes to extend ECV-UFT combinations in the outlined primary areas of focus as future research work.

One of the problems facing public education institutions in Brazil is the question of the correct handling and treatment of waste electrical and electronic equipment (WEEE). Being that these institutions are part of the public sector, they should adhere to Decree no. 99,658/1990 for the disposal of their goods. However, this decree is not completely in accordance with the Brazilian National Solid Waste Policy (PNRS), especially when considering the regulations for disposal of public goods. Thus, these institutions have no WEEE management model which encompasses not only the Decree but also the PNRS. An example of this situation can be found at the Federal University of Itajubá (UNIFEI) in Minas Gerais, Brazil. Due to the lack of such a management model, the university warehouse is at full capacity and unable to receive additional electronic equipment. Therefore, the objective of this study is to create a management model for WEEE to be used at public education institutions using the guidelines set forth in both the Decree and the PNRS. An action research investigation was performed at UNIFEI which relied upon two improvement and learning cycles to deal with all the WEEE found at the university. The first was undertaken at the university warehouse and the second at other sectors within the institution. In addition to the practical results obtained by properly disposing of 474 WEEE products, this study showed that action research is an adequate management tool for public institutions looking to deal with problems of this nature, being that these institutions are almost always subject to bureaucratic controls with respect to their public property, and expected to follow rigorous legislation that is often times controversial.

The objective of this paper is to study and report upon the elaboration of a selective waste collection program in a Brazilian city through action research; the overarching goal is that all knowledge generated may serve as a basis of information and reference to aid in decision making for similar programs globally. The municipality chosen was São Lourenço in the state of Minas Gerais. The implementation of the selective waste collection program happened over the course of multiple improvement and learning cycles, and enabled many environmental, economic and social benefits for all of the project¿s stakeholders. Eighty-nine tons of potentially recycled material were sent to recycling processes rather than being disposed of in a landfill. No great difficulties were observed for the use of action research as a method, but some challenges were encountered and overcome during the whole process, due to the lack of structure and confidence on part of the population, in relation to the selective collection program. The choice for action research as the methodology and the use of improvement and learning cycles proved to increase the project¿s overall efficiency, making it possible to make decisions more quickly, generating better results, and enabling replications of good decisions and correction of errors from one cycle to the next.

With the National Policy on Solid Waste it has become mandatory to implement selective waste collection programs and that such programs should be efficient. In both implementation and improvement of the selective waste collection programs that already exist, we must consider mainly three questions: who will act as the collection agent; which selective waste collection model will be used and how to effectively plan the collection routes. One way to optimize the collection routes is using a Geographic Information System (GIS). Therefore, in this paper it has been planned and implemented a selective waste collection in São Lourenço, Minas Gerais, using a GIS to calculate the routes. Today, there are two collection routes working, allowing the whole population of the city to be served by the selective waste collection program. Furthermore, it has been noticed that the door-to-door collection mode is not the optimal in the beginning of the implementation, and the awareness from the population was the main barrier in the implementation.