1. FIRST CYCLE - BACHELOR'S DEGREE
  2. FACULTY OF ENGINEERING
  3. INDUSTRIAL ENGINEERING DEPARTMENT
  4. 255 Industrial Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
IENG 435HEURISTIC METHODS IN PROBLEM SOLVING3 + 05th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective A large part of industrial engineering research topics cover NP-Hard problems. Today, these problems may not be solved by mathematical optimization techniques that give precise results. For this reason, it is aimed to introduce / teach frequently preferred heuristic algorithms and application areas in the solution of large-scale optimization problems in the literature. It is aimed that the student taking the course will be able to use / adapt heuristic methods effectively in solving NP-Difficult problems in the field of industrial engineering.
Course Content Introduction to optimization problems, NP-Hard problems, Constructive heuristic algorithms, solution development structures, parametric heuristic methods, evolutionary computational algorithms and swarm intelligence algorithms.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Introduces NP-Hard problems.
2Provides theoretical and practical knowledge about various heuristic algorithms.
3The ability to develop solutions to NP-Hard problems by using heuristic methods.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12PO 13
LO 001             
LO 002             
LO 003             
Sub Total             
Contribution0000000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Assignments4624
Mid-terms11010
Final examination11414
Presentation / Seminar Preparation11414
Report / Project12626
Total Work Load

ECTS Credit of the Course





130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Spring1CAN BERK KALAYCI
Details 2021-2022 Spring1CAN BERK KALAYCI


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
IENG 435 HEURISTIC METHODS IN PROBLEM SOLVING 3 + 0 1 Turkish 2023-2024 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Assoc. Prof. Dr. CAN BERK KALAYCI cbkalayci@pau.edu.tr TEK A0109 %70
Goals A large part of industrial engineering research topics cover NP-Hard problems. Today, these problems may not be solved by mathematical optimization techniques that give precise results. For this reason, it is aimed to introduce / teach frequently preferred heuristic algorithms and application areas in the solution of large-scale optimization problems in the literature. It is aimed that the student taking the course will be able to use / adapt heuristic methods effectively in solving NP-Difficult problems in the field of industrial engineering.
Content Introduction to optimization problems, NP-Hard problems, Constructive heuristic algorithms, solution development structures, parametric heuristic methods, evolutionary computational algorithms and swarm intelligence algorithms.
Topics
WeeksTopics
1 Introduction
2 Introduction to Optimization Problems
3 Simulated Annealing
4 Tabu Search
5 Genetic Algorithms
6 Variable Neighborhood Search
7 Ant colony Algorithm
8 Midterm exam
9 Artificial Immune System Algorithm
10 Differential Evolution Algorithm
11 Particle Swarm Optimization
12 Artificial Bee Colony Algorithm
13 Artificial Neural Networks and other heuristic approaches
14 Presentation of projects
Materials
Materials are not specified.
Resources
ResourcesResources Language
1. Yapay Zeka Optimisazyon Algoritmaları, Derviş Karaboğa, Nobel Yayın Dağıtım, 2011. Türkçe
2. Modern Sezgisel Teknikler ve Uygulamaları, Dr. Tunçhan Cura, Papatya Yayıncılık Eğitim 2008. Türkçe
3. Handbook of Metaheuristics (International Series in Operations Research & Management Science), Michel Genderau, Jean-Yves Potvin, Springer, 2012. Türkçe
4. Modern Heuristic Search Methods, V. J. Rayward-Smith, I. H. Osman, C. R. Reeves, G. D. Smith, Wiley, 1996.Türkçe
5. Metaheuristics for Hard Optimization, J. Dreo, P. Siarry, A. Petrowski, E. Taillard, Springer, 2003.Türkçe
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes