Credit Points: 3.5
Prerequisites: deterministic models in Operations Research
Description of the course:
The course deals with ideas and methods for analysis of optimization problems in discrete and continuous domain. Analytical and numerical procedures are studied, some with computer applications. Meta-heuristic methods for combinatorial optimization are studied.
Topics of the course:
Introduction, optimization problem formulation, and applications in the area of industrial engineering. Local search vs. global search. Optimization methods for single-variable functions. Optimization in continuous domain. Convexity. Necessary and sufficient conditions of optimality. Gradient methods. Constrained problems. The method of Lagrange. Kuhn-Tucker conditions. Dual problem. Optimization in discrete domain. Enumeration methods and dynamic programming. Applications of dynamic programming. Simulated annealing method. Neural-network based methods. Genetic algorithms. Properties of the heuristic methods.