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Policy Scenario Goal Programming×Sztochasztikus Célprogramozás×
TudományterületSzimulációSzimuláció
MódszercsaládProcess / pipelineProcess / pipeline
Keletkezés éve1961 (goal programming); policy scenario application 1980s–present1968
MegalkotóCharnes, A., Cooper, W. W. (goal programming); policy scenario integration developed in OR/policy literatureContini, B. (building on Charnes & Cooper's chance-constrained programming)
TípusOptimization under multiple conflicting goals across policy scenariosStochastic multi-goal optimization
AlapműCharnes, 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 ↗
Alternatív nevekPSGP, Policy GP, Scenario-based Goal Programming, Multi-scenario Goal ProgrammingSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming
Kapcsolódó56
ÖsszefoglalóPolicy 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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ScholarGateMódszerek összehasonlítása: Policy Scenario Goal Programming · Stochastic Goal Programming. Letöltve 2026-06-18, forrás: https://scholargate.app/hu/compare