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확률적 목표 계획법×확률적 선형 계획법×
분야시뮬레이션시뮬레이션
계열Process / pipelineProcess / pipeline
기원 연도19681955
창시자Contini, B. (building on Charnes & Cooper's chance-constrained programming)George B. Dantzig
유형Stochastic multi-goal optimizationStochastic optimization model
원전Contini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗Dantzig, G. B., & Madansky, A. (1961). On the solution of two-stage linear programs under uncertainty. Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1, 165–176. link ↗
별칭SGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal ProgrammingSLP, Stochastic LP, Linear Programming under Uncertainty, Two-Stage SLP
관련65
요약Stochastic 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.Stochastic Linear Programming (SLP) extends classical linear programming to settings where some model parameters — costs, demands, resource availability — are uncertain and modeled as random variables. By optimizing expected costs over a probability distribution of scenarios, SLP produces decisions that remain feasible and near-optimal across a range of possible futures rather than for a single assumed state of the world.
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ScholarGate방법 비교: Stochastic Goal Programming · Stochastic Linear Programming. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare