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COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
COMBINATORIAL ALGORITHMS AND META HEURISTICS END628 - 3 + 0 10

TYPE OF COURSE UNITCompulsory Course
LEVEL OF COURSE UNITDoctorate Of Science
YEAR OF STUDY-
SEMESTER-
NUMBER OF ECTS CREDITS ALLOCATED10
NAME OF LECTURER(S)Professor Berna Dengiz
LEARNING OUTCOMES OF THE COURSE UNIT At the end of this course, the students;
1) Gain an ability to apply knowledge of mathematics, science, and engineering
2) Gain an ability to design and conduct experiments, as well as to analyze and interpret data
3) Gain an ability to design a system, component, or process to meet desired needs within realistic
4) Gain an ability to identify, formulate, and solve engineering problems
5) Gain an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
MODE OF DELIVERYFace to face
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTEND537 Heuristic Methods
COURSE DEFINITIONStructures of algorithms, algorithms in combinatorics, structure of combinatorics, combinartorial problems, complexity classes, data structures, the algorithm design techniques, combinatorial generation, backtracking algorithms, heuristic search algorithms, advanced and hybrid heuristic algorithms and problem specific applications.
COURSE CONTENTS
WEEKTOPICS
1st Week Introduction to Combinatorial Optimization
2nd Week Introduction to metaheuristics
3rd Week Solution based metaheuristics
4th Week Regenerative metaheuristics
5th Week Regenerative metaheuristics
6th Week Simulated Annealing Algorithm
7th Week Simulated Annealing Algorithm
8th Week Midterm
9th Week Tabu Search Algortihm
10th Week Genetic Algorithm
11th Week Genetic Algorithm
12th Week Genetic Algorithm
13th Week Evaluating the performance of the metaheuristics
14th Week Project presentation
RECOMENDED OR REQUIRED READINGRayward-Smith, V.J., Osman, I.H., Reeves, C.R.(Editors), (1996), Modern Heuristic Search Methods, Wiley.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODSLecture,Questions/Answers,Practice,Problem Solving
ASSESSMENT METHODS AND CRITERIA
 QuantityPercentage(%)
Mid-term125
Assignment310
Quiz410
Practice515
Total(%)60
Contribution of In-term Studies to Overall Grade(%)60
Contribution of Final Examination to Overall Grade(%)40
Total(%)100
ECTS WORKLOAD
Activities Number Hours Workload
Midterm exam122
Preparation for Quiz
Individual or group work14798
Preparation for Final exam12525
Course hours14342
Preparation for Midterm exam12525
Laboratory (including preparation)
Final exam122
Homework814112
Total Workload306
Total Workload / 3010,2
ECTS Credits of the Course10
LANGUAGE OF INSTRUCTIONTurkish
WORK PLACEMENT(S)No
  

KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
LO1LO2LO3LO4LO5
K1        X  
K2  X   X     X   X
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K4          X
K5  X         X
K6      X    
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K11