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Stohastično linearno programiranje×Stohastičko programiranje ciljeva×
OblastSimulacijaSimulacija
PorodicaProcess / pipelineProcess / pipeline
Godina nastanka19551968
TvoracGeorge B. DantzigContini, B. (building on Charnes & Cooper's chance-constrained programming)
TipStochastic optimization modelStochastic multi-goal optimization
Temeljni izvorDantzig, 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 ↗Contini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗
Drugi naziviSLP, Stochastic LP, Linear Programming under Uncertainty, Two-Stage SLPSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming
Srodne56
SažetakStochastic 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.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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ScholarGateUporedite metode: Stochastic Linear Programming · Stochastic Goal Programming. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare