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Combinatorial Optimization & Metaheuristics

 

Major topics:

            Section 1: Analysis of algorithms

1-      Introduction to algorithms

2-      Asymptotic analysis

3-      Time complexity function

4-      The theory of NP-completeness

5-      Finite state machines

          Section 2: Metha heuristics algorithms

1-      Introduction to metha heuristic methods

2-      Simulated Annealing algorithm

3-      Tabu Search algorithm

4-      Ant Colony algorithm

5-      Genetic Algorithms

6-      Neural Networks

 

    Prescribed Texts:

 

           Section 1:

1-      Combinatorial Optimization: Algorithms and Complexity, Papadimitriou and Steiglitz, Prentice- Hall , 1998.

2-      An Introduction to Algorithm, Thomas H. Cormen  et al., 2000.

3-      Discrete Mathematics, S. Epp, 1999

4-      Algorithms, Skienna, 2000

        Section 2:

1-      "مبانی شبکه های عصبی" جلد اول، محمد باقر منهاج، انتشارات دانشگاه صنعتی امیرکبیر

2-      Kirkpatrick, S., Gelatt, C. D. and Vecchi, M.P., “Optimization by Simulated Annealing”,Science, Vol. 220, No. 4598, 1983

3-      Dorigo M., Stutzle T. "Ant colony optimization", 2004

4-      Glover F. and Laguna M. "Tabu search", Kluwer academic publisher

5-      Sivanandam S.M. and Deepa S. N. "Introduction to genetic algorithms",2007

1-      Introduction to metha heuristic methods

2-      Simulated Annealing algorithm

3-      Tabu Search algorithm

4-      Ant Colony algorithm

5-      Genetic Algorithms

6-      Neural Networks

 

 .

 

 

Prerequisites: 

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Grading Policy: 

 

1-    Assignment: 10%

2-    Research: 50%

1-   Algorithm design & programming: 20%

2-   Analysis of experimental results: 17.5%

3-   Documentation: 12.5%

3-    Final Exam: 40%

Time: 

Sundays & Tuesdays

15-16:30 pm

 

 

 

Term: 
Fall_2012
Grade: 
graduate

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