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برنامه‌ریزی خطی مقاوم×بهینه‌سازی چندهدفه استوار×
حوزهشبیه‌سازیشبیه‌سازی
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش1999–20042006
پدیدآورBen-Tal, A. and Nemirovski, A.; further developed by Bertsimas, D. and Sim, M.Deb, K. & Gupta, H.
نوعUncertainty-robust linear optimizationOptimization framework
منبع بنیادینBertsimas, D., Sim, M. (2004). The price of robustness. Operations Research, 52(1), 35–53. DOI ↗Deb, K., & Gupta, H. (2006). Introducing robustness in multi-objective optimization. Evolutionary Computation, 14(4), 463–494. DOI ↗
نام‌های دیگرRLP, Robust LP, Tractable Robust LP, Uncertainty-Set LPRMOO, Robust MOO, Robust Pareto Optimization, Uncertainty-Robust Multi-Objective Optimization
مرتبط54
خلاصهRobust Linear Programming (RLP) extends classical linear programming to handle uncertainty in problem data — cost coefficients, constraint coefficients, or right-hand sides — by requiring solutions to remain feasible and near-optimal across all realizations of uncertain parameters within a defined uncertainty set. It replaces probabilistic assumptions with worst-case guarantees, making it practical when distributional knowledge is limited.Robust Multi-Objective Optimization (RMOO) is a framework for finding solutions that simultaneously optimize multiple conflicting objectives while remaining insensitive to perturbations in decision variables or problem parameters. Unlike classical MOO, RMOO explicitly incorporates uncertainty into the optimization loop, producing a robust Pareto front whose members perform well not only at the nominal design point but also across a neighbourhood of plausible operating conditions.
ScholarGateمجموعه‌داده
  1. v1
  2. 2 منابع
  3. PUBLISHED
  1. v1
  2. 2 منابع
  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Robust Linear Programming · Robust Multi-Objective Optimization. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare