CEE 5290 Heuristic Methods for Optimization
Lecture: MWF 12:20pm-1:10pm OLH 165
Fall. 3-4 credits, variable. Cross-listed with CS 5722 and ORIE 5330.
Prerequisites: graduate standing or CS 2110 /ENGRD 2110 ; ENGRD 3200 or permission of instructor.
Teaches heuristic search methods including simulated annealing, tabu search, genetic algorithms, derandomized evolution strategy, and random walk developed for optimization of combinatorial- and continuous-variable problems. Application project options include wireless networks, protein folding, job shop scheduling, partial differential equations, satisfiability, or independent projects. Statistical methods are presented for comparing algorithm results. Advantages and disadvantages of heuristic search methods for both serial and parallel computation are discussed in comparison with other optimization algorithms.