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확률적 목표 계획법×다목적 목표 계획법×
분야시뮬레이션시뮬레이션
계열Process / pipelineProcess / pipeline
기원 연도19681961
창시자Contini, B. (building on Charnes & Cooper's chance-constrained programming)Charnes, A. and Cooper, W. W.
유형Stochastic multi-goal optimizationMathematical programming / multi-criteria optimization
원전Contini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗Charnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 978-0471148258
별칭SGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal ProgrammingMOGP, Multi-goal programming, Vector goal programming, Multi-criteria goal programming
관련64
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.Multi-Objective Goal Programming (MOGP) is a mathematical programming technique that simultaneously pursues several aspirational targets by minimizing weighted deviations from each goal. Rooted in Charnes and Cooper's original goal programming framework (1961), MOGP extends it to handle multiple competing objectives, making it indispensable in operations research, supply chain design, resource allocation, and policy analysis where decision-makers must satisfy — or come close to — multiple conflicting requirements at once.
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ScholarGate방법 비교: Stochastic Goal Programming · Multi-objective goal programming. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare