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حوزهشبیه‌سازیشبیه‌سازی
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش1961 (goal programming); policy scenario application 1980s–present1968
پدیدآورCharnes, A., Cooper, W. W. (goal programming); policy scenario integration developed in OR/policy literatureContini, B. (building on Charnes & Cooper's chance-constrained programming)
نوعOptimization under multiple conflicting goals across policy scenariosStochastic multi-goal optimization
منبع بنیادینCharnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 9780471153405Contini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗
نام‌های دیگرPSGP, Policy GP, Scenario-based Goal Programming, Multi-scenario Goal ProgrammingSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming
مرتبط56
خلاصهPolicy Scenario Goal Programming (PSGP) integrates goal programming optimization with policy scenario analysis to evaluate how well competing policy objectives can be achieved under distinct future conditions. Decision-makers define multiple goals and several plausible policy scenarios, then solve a goal programming model for each scenario to identify which policy strategies best satisfy priority targets across the full scenario space.Stochastic Goal Programming (SGP) extends classical goal programming to handle uncertainty in goal targets, constraint coefficients, or right-hand-side parameters. By incorporating probabilistic constraints and stochastic objective components, it finds solutions that satisfy multiple goals at acceptable probability levels, making it suitable for decision problems where data are inherently uncertain or variable.
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ScholarGateمقایسهٔ روش‌ها: Policy Scenario Goal Programming · Stochastic Goal Programming. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare