Course Overview: Heuristics and Metaheuristics in Operations Research
Explore the practical issues, methods of assessment, recommended textbooks, course catalogue description, aims, and objectives of the course taught by Asst. Prof. Dr. Ahmet NVEREN on Heuristics and Metaheuristics. The course delves into various heuristic methods, metaheuristics, and optimization tec
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Metaheuristics and Hybrid Approaches in Multi-Objective Optimization
Multi-objective optimization involves solving complex problems with conflicting objectives, such as minimizing makespan and tardiness in flow shop scheduling. Pareto Optimal Solutions are sought, where improving one objective cannot be done without worsening another. Metaheuristics like S and P meth
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Parallel Approaches for Multiobjective Optimization in CMPE538
This lecture provides a comprehensive overview of parallel approaches for multiobjective optimization in CMPE538. It discusses the design and implementation aspects of algorithms on various parallel and distributed architectures. Multiobjective optimization problems, often NP-hard and time-consuming
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Metaheuristic Algorithms: Search Strategies and Solution Space
Metaheuristics offer a direct search approach to finding solutions, bypassing mathematical models. By iteratively improving feasible solutions, these algorithms balance diversification and intensification. Understanding solution representation and neighborhood structures is key, as well as navigatin
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Nature-Inspired Population-Based Metaheuristics and Optimization Techniques
This comprehensive guide delves into various population-based metaheuristics and nature-inspired optimization techniques such as evolutionary algorithms, swarm intelligence, and artificial immune systems. It covers concepts like genetic algorithms, ant colony optimization, particle swarm optimizatio
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Metaheuristics for Multi-Objective Optimization and Hybrid Approaches
Discover the world of multi-objective optimization with NP-hard conflicting objectives, Pareto optimal solutions, and metaheuristics. Learn about fitness assignment, diversity preservation, and dominance-based strategies for finding Pareto optimal sets. Explore hybrid metaheuristics combining variou
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Local Search and Genetic Algorithms
Explore the concepts of local search, its variations, and how local search-based metaheuristics like genetic algorithms aim to avoid local optima, explore a broader search space, and find global optimum solutions efficiently.
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Metaheuristics in Evolutionary Algorithms and Genetic Programming
Discover the principles of population-based metaheuristics such as genetic algorithms and evolutionary programming. Explore common concepts in evolutionary algorithms and delve into genetic programming, a modern approach involving program-based solutions. Witness the evolution and application of gen
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