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정책 시나리오 목표 계획법×확률적 목표 계획법×
분야시뮬레이션시뮬레이션
계열Process / pipelineProcess / pipeline
기원 연도1961 (goal programming); policy scenario application 1980s–present1968
창시자Charnes, A., Cooper, W. W. (goal programming); policy scenario integration developed in OR/policy literatureContini, B. (building on Charnes & Cooper's chance-constrained programming)
유형Optimization under multiple conflicting goals across policy scenariosStochastic multi-goal optimization
원전Charnes, 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 ↗
별칭PSGP, Policy GP, Scenario-based Goal Programming, Multi-scenario Goal ProgrammingSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming
관련56
요약Policy 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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