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البحث التابو متعدد الأهداف (MOTS)×الخوارزمية الجينية متعددة الأهداف (MOGA)×
المجالالمحاكاةالمحاكاة
العائلةProcess / pipelineProcess / pipeline
سنة النشأة19971984
صاحب الطريقةHansen, M. P.; building on Glover (1989) Tabu SearchSchaffer, J. D. (early MOGA); Goldberg, D. E. (GA foundations)
النوعMetaheuristic multi-objective optimizationPopulation-based evolutionary optimizer
المصدر التأسيسيHansen, M. P. (1997). Tabu search for multiobjective optimization: MOTS. Presented at the 13th International Conference on Multiple Criteria Decision Making (MCDM), Cape Town, South Africa. link ↗Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Addison-Wesley. ISBN: 9780201157673
الأسماء البديلةMOTS, Multi-criteria Tabu Search, Pareto Tabu Search, TSMOOMOGA, Multi-objective GA, Evolutionary multi-objective optimization, EMO
ذات صلة54
الملخصMulti-objective Tabu Search (MOTS) is a metaheuristic algorithm that extends the classic Tabu Search framework to simultaneously optimize two or more conflicting objective functions. Instead of a single optimum, it seeks to approximate the Pareto front — the set of solutions where no objective can be improved without worsening another — making it suitable for complex combinatorial and continuous optimization problems in engineering, logistics, and operations research.A Multi-Objective Genetic Algorithm (MOGA) is an evolutionary computation method that evolves a population of candidate solutions toward a Pareto-optimal front, simultaneously optimizing two or more conflicting objective functions. It avoids collapsing trade-offs into a single score, instead producing a set of non-dominated solutions for the decision-maker to choose among.
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ScholarGateقارن الطرق: Multi-objective Tabu Search · Multi-objective genetic algorithm. استُرجع بتاريخ 2026-06-15 من https://scholargate.app/ar/compare