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التحسين بالزخم الجسيمي متعدد الأهداف (MOPSO)×محاكاة المعادن المتباينة متعددة الأهداف (MOSA)×
المجالالمحاكاةالمحاكاة
العائلةProcess / pipelineProcess / pipeline
سنة النشأة20041992–1998
صاحب الطريقةCoello Coello, C. A., Pulido, G. T., & Lechuga, M. S.Serafini, P.; Czyzak, P. and Jaszkiewicz, A.
النوعPopulation-based swarm metaheuristicMetaheuristic / Pareto-based optimizer
المصدر التأسيسيCoello Coello, C. A., Pulido, G. T., & Lechuga, M. S. (2004). Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8(3), 256–279. DOI ↗Czyzak, P., Jaszkiewicz, A. (1998). Pareto simulated annealing — a metaheuristic technique for multiple-objective combinatorial optimization. Journal of Multi-Criteria Decision Analysis, 7(1), 34–47. DOI ↗
الأسماء البديلةMOPSO, Multi-objective PSO, Pareto PSO, Vector-evaluated PSOMOSA, Multi-Criteria Simulated Annealing, Pareto Simulated Annealing, PSA
ذات صلة55
الملخصMulti-Objective Particle Swarm Optimization (MOPSO) is a swarm-intelligence metaheuristic that extends the original Particle Swarm Optimization (PSO) to handle multiple conflicting objective functions simultaneously. It maintains an external Pareto archive and uses dominance-based selection to guide a population of candidate solutions toward the true Pareto front without requiring a priori preference information.Multi-Objective Simulated Annealing (MOSA) extends the classical simulated annealing metaheuristic to problems with two or more conflicting objective functions. Instead of converging to a single optimum, MOSA explores the solution space stochastically and maintains an archive of non-dominated (Pareto-optimal) solutions, offering decision-makers a diverse trade-off front rather than one prescribed answer.
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ScholarGateقارن الطرق: Multi-objective particle swarm optimization · Multi-objective simulated annealing. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare