END 557E - Heuristic Optimization

Course Objectives

1. To introduce variety of heuristic methods with mathematics and field of application.
2. Modeling heuristic algorithms in optimization
3. To allow modeling and implementation of one method in an optimization field.

Course Description

Business problems like machine scheduling, portfolio selection, resource allocation and supply chain network design are considered NP-complete problems. Though classical optimization methods are used in modeling there is no known efficient way to locate a solution in the first place. Decision makers are happy with finding a near-optimal solution using Heuristic approaches. This course will be presenting the most recent meta-heuristic techniques using combinatorial and continuous samples. Simulated Annealing, Tabu Search, Genetic Algorithm, Ant Colony, Swarm Intelligence will be focused, but an overview of other methods will be given. Attendees will gain knowledge of where and how to use heuristic methods in addition to reading comparisons with classical algorithms in selected papers.