Courses with significant overlap with this course:

Semester of last offering:

Date of approval: dd-mmm-yyyy

Prerequisites:IME605A 

Course Contents

Review of linear and integer linear programming. Multistage decision models: Dynamic programming. Network flow problems: Shortest path, maximum flow and minimum cost flow problems; Network optimization. Multi objective decision models: Analytic hierarchy and network processes. Nonlinear programming: Un constrained optimization; Lagrangian relaxation and KKT conditions; Convex optimization; Search, gradient and penalty based methods; Quadratic programming. Metaheauristics and their applications to combinatorial optimization problems such as scheduling and allocation problems. Stochastic decision models: Markov chains; Queues and queuing networks.