Description of Individual Course Units
 Course Unit Code Course Unit Title Type of Course Unit Year of Study Semester Number of ECTS Credits 9204045442017 Heuristic Methods Elective 1 2 4
Level of Course Unit
Second Cycle
Objectives of the Course
A large part of the research area of industrial engineering includes NP-hard problems. These problems usually cannot be solved by exact optimization techniques. In recent years, heuristic techniques will be effectively deal with these problems. In this course, heuristic techniques and its application areas will be introduced.
Name of Lecturer(s)
DR. ÖĞR. ÜYESİ U. GÖKAY ÇİÇEKLİ
Learning Outcomes
 1 Student learns the basic concepts of heuristic methods 2 Student gains the ability of identifying problems and finding solutions by using a mathematical model. 3 Student gains the ability of improving classical and heuristic methods for the solution of NP-Hard problems.
Mode of Delivery
Evening Education
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
Introduction to Optimization problems, NP-Complete problems, Lagrangean Relaxation and Lagrangean Heuristics, Classical Construction Heuristics (Savings, Nearest Neighbor, Greedy) Classical Improvement Heuristics (Node Insertion, k-opt, or-opt), Meta-heuristic Methods (Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony) will be introduced.
Weekly Detailed Course Contents
 Week Theoretical Practice Laboratory 1 Introduction to Optimization Problems 2 NP-Complete problems 3 Lagrange multipliers and heuristics 4 Classical Heuristic Methods (Savings) 5 Classical Heuristic Methods (Nearest Neighbor) 6 Classical Heuristic Methods (Greedy) 7 Improving heuristics (adding node, k-opt, or-opt) 8 Midterm Exam 9 Improving heuristics (adding node, k-opt, or-opt) 10 Parametric Heuristic Methods 11 Parametric Heuristic Methods 12 Project Presentations 13 Project Presentations 14 Project Presentations 15 Project Presentations 16 Final Exam
• Wayne L. Winston (2003) Operations Research: Applications and Algorithms, Yayınevi: Cengage: Brooks / Cole. • All related articles
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
 Term (or Year) Learning Activities Quantity Weight SUM 0 End Of Term (or Year) Learning Activities Quantity Weight SUM 0 SUM 0
Language of Instruction
Turkish
Work Placement(s)
None