Operations Research 2

Course code MATH3830Units 10Level 3000Faculty of Science and Information TechnologySchool of Mathematical and Physical Sciences

Often known as the 'science of better', Operations Research (OR) is the cornerstone of effective decision making. OR has enhanced organisations and experiences all around us. From more cost effective scheduling of airline crews to the design of less intrusive cancer radiation therapy treatments, from two-person start-ups to Fortune 500 companies, from global resource planning decisions to optimizing local postal delivery routes, all benefit directly from OR.

This course is intended for students looking to advance their fundamental knowledge of OR techniques as seen in MATH2730. The course delves into both practical and theoretical aspects of established OR techniques and results. The course will better equip students to judge the applicability of methods for given problems, and answer questions as to why two seemingly similar problems differ dramatically with respect to tractability. By the end of the course students will be able to apply known OR techniques effectively and also, develop their own solutions for newer, more challenging problems. Throughout, use will be made of relevant widely used software packages.

Available in 2014

Callaghan CampusSemester 1
Previously offered in 2013, 2012, 2011
ObjectivesOn successful completion of this course, students will have:

1. A thorough understanding of the quantitative techniques and theory behind Operations Research.
2. An advanced appreciation of the use of a mathematical model as a way of encapsulating and analysing a complex situation.
3. An advanced repertoire of problem-solving skills that is both analytical and flexible.
ContentThe course will cover two main areas:
1.Nonlinear programming, including
a.necessary and sufficient conditions for optimality,
b.solution methods, and
c.numerical solution; and
2. Probability models in operations research, with topics selected from
a.queueing theory,
b.revenue management,
c.Markov decision processes, and
d.inventory control.
For each topic, applications, modelling, and methods will be explored. Appropriate software packages for modelling and solutions of problems will be covered.
Replacing Course(s)NA
TransitionNA
Industrial Experience0
Assumed KnowledgeAny 2000 level mathematics course.
Modes of DeliveryInternal Mode
Teaching MethodsLecture
Tutorial
Computer Lab
Assessment Items
Essays / Written Assignments
Examination: Formal
Contact HoursLecture: for 3 hour(s) per Week for Full Term
Timetables2014 Course Timetables for MATH3830