Heuristic Optimization is a relatively new trend in analyzing and solving difficult integer and combinatorial optimization problems, where optimal solutions are costly or impossible to obtain in reasonable time and therefore near-optimal solutions are usually acceptable. This course starts with introducing the basic heuristic optimization concept and methodology in combinatorial optimization. This is followed by the presentation and discussion of widely-used heuristic optimization algorithms such as as simulated annealing, neural networks, genetic algorithms, tabu search, evolutionary algorithms and ant-colony algorithms. Problem-specific applications of these techniques are also covered. An important part of this course is the implementation of one or more of these algorithms in a programming language of each student's choice. (Knowledge of Basic programming skills in a computer is recommended)