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Metaheuristic computing is a popular methodology discovered for resolving optimization problems in engineering design and applied in various fields such as engineering, business, transportation, and even social sciences. Metaheuristic computing mimics bio-inspired techniques for constructing several metaheuristic algorithms that assist in finding effective and high-quality solutions.
Metaheuristic computing is utilized in a wide range of applications such as marketing, finance, computing, management, intelligent traffic systems, engineering, health care, telecommunication, logistics, agriculture, and medicine. Currently, metaheuristic computing is applied for single, stochastic, and multi-objective approaches for metaheuristic optimization problems by learning heuristics. Future work on metaheuristic computing focusing on enhancing the exploration and exploitation phase, power flow, optimal tuning of power systems in a broad range of engineering problems.
Metaheuristic computing PHD thesis represents design, evaluation, algorithms, application of metaheuristics to real-world problems, and future scopes in metaheuristic optimization. The following list comprises PHD thesis topics on metaheuristic computing to pose the large scale research spaces and great opportunities for researchers to figure out a diverse range of problems in real-world applications.
