IE505 HEURISTIC SEARCH

Course Code:5680505
METU Credit (Theoretical-Laboratory hours/week):3 (3.00 - 0.00)
ECTS Credit:8.0
Department:Industrial Engineering
Language of Instruction:English
Level of Study:Graduate
Course Coordinator:Prof.Dr. NUR EVİN ÖZDEMİREL
Offered Semester:Fall or Spring Semesters.

Course Objectives

At the end of the course, the students will be able to

1. understand principles of conventional heuristic search algorithms for solving combinatorial optimization problems.

2. understand, develop, and implement metaheuristic search algorithms for solving combinatorial optimization problems.

3. comprehend computational complexity of heuristic search algorithms and evaluate their performance empirically.


Course Content

Heuristic search approaches for solving difficult combinatorial problems. Categorization of heuristic search techniques. Traditional heuristics for combinatorial optimization problems. Meta heuristics including simulate annealing, tabu search and evolutionary algorithms. Constraint handling techniques. Computational complexity of heuristics.


Course Learning Outcomes

At the end of the course, the students will be able to

1.1. learn basic types of conventional construction and improvement heuristic algorithms.

1.2. comprehend computational complexity and understand empirical performance of conventional heuristic algorithms.

2.1. learn basic principles and operators of metaheuristics such as simulated annealing, tabu search, evolutionary algorithms, and swarm intelligence.

2.2. develop and implement a metaheuristic search algorithm for an optimization problem of their choice.

3.1. use design of experiments to fine tune a metaheuristic by adjusting the algorithm and problem parameters.

3.2. evaluate the performance of a metaheuristic search algorithm empirically and compare it with its competitors.