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: | Assist.Prof.Dr NADER GHAFFARINASAB |
| 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.
Program Outcomes Matrix
| Contribution | |||||
| # | Program Outcomes | No | Yes | ||
| 1 | Specialize with advanced knowledge in selected areas of Industrial Engineering; such as Production and Operations Management, Supply Chain Management, Business Analytics and Information Systems, Decision Sciences and Operational Research, Quality Management, Human Factors and Ergonomics, and Strategy and Industrial Economics. | ✔ | |||
| 2 | Have advanced ability to formulate and solve industrial engineering problems. | ✔ | |||
| 3 | Be able to systematically acquire new scientific knowledge to design and improve socio-technical systems. | ✔ | |||
| 4 | Be able to conduct scientific research in industrial engineering. | ✔ | |||
| 5 | Be able to apply critical reasoning in their professional careers. | ✔ | |||
| 6 | Appreciate the academics ethics. | ✔ | |||