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Robusti tavoiteohjelmointi×Stokastinen tavoiteohjelmointi×
TieteenalaSimulointiSimulointi
MenetelmäperheProcess / pipelineProcess / pipeline
Syntyvuosi1961 (GP); 1990s (robust extension)1968
KehittäjäCharnes, A. & Cooper, W. W. (goal programming); Mulvey, J. M. et al. (robust optimization framework)Contini, B. (building on Charnes & Cooper's chance-constrained programming)
TyyppiMathematical programming under uncertaintyStochastic multi-goal optimization
AlkuperäislähdeCharnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 9780471155041Contini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗
RinnakkaisnimetRGP, Goal Programming under Uncertainty, Robust GP, Uncertainty-Aware Goal ProgrammingSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming
Liittyvät56
TiivistelmäRobust Goal Programming (RGP) extends classical goal programming to handle uncertain or ambiguous model parameters. Instead of minimizing deviations from crisp targets, it seeks solutions that remain feasible and near-optimal across a range of plausible scenarios or uncertain data realizations. RGP is particularly valuable in planning problems where goals are aspirational and input data carries inherent variability or estimation error.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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ScholarGateVertaile menetelmiä: Robust goal programming · Stochastic Goal Programming. Haettu 2026-06-15 osoitteesta https://scholargate.app/fi/compare