Topic outline

  • M0 Introduction

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  • M1 Fundamentals of Heuristic Optimization

  • M2 Optimization Problem Formulation and Search Space Representation

  • M3 Local Search and Neighborhood-Based Optimization

  • M4 Greedy and Constructive Heuristic Methods

  • M5 Randomized Search and Stochastic Optimization

  • M6 Simulated Annealing for Combinatorial Optimization

  • M7 Tabu Search and Memory-Based Optimization

  • M8 Midterm Examination

  • M9 Genetic Algorithms for Optimization

  • M10 Evolutionary and Population-Based Optimization

  • M11 Ant Colony Optimization

  • M12 Particle Swarm Optimization

  • M13 Hybrid and Adaptive Heuristic Methods

  • M14 Performance Evaluation of Heuristic Algorithms

  • M15 Experimental Benchmarking and Comparative Analysis

  • M16 Final Examination