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محاكاة المعادن المتباينة متعددة الأهداف (MOSA)×التحسين بالزخم الجسيمي متعدد الأهداف (MOPSO)×
المجالالمحاكاةالمحاكاة
العائلةProcess / pipelineProcess / pipeline
سنة النشأة1992–19982004
صاحب الطريقةSerafini, P.; Czyzak, P. and Jaszkiewicz, A.Coello Coello, C. A., Pulido, G. T., & Lechuga, M. S.
النوعMetaheuristic / Pareto-based optimizerPopulation-based swarm metaheuristic
المصدر التأسيسيCzyzak, 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 ↗Coello 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 ↗
الأسماء البديلةMOSA, Multi-Criteria Simulated Annealing, Pareto Simulated Annealing, PSAMOPSO, Multi-objective PSO, Pareto PSO, Vector-evaluated PSO
ذات صلة55
الملخصMulti-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.Multi-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.
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ScholarGateقارن الطرق: Multi-objective simulated annealing · Multi-objective particle swarm optimization. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare