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Stochastic Goal Programming×Mitmeotstarbeline eesmärgiprognoosimine×
ValdkondSimulatsioonSimulatsioon
PerekondProcess / pipelineProcess / pipeline
Tekkeaasta19681961
LoojaContini, B. (building on Charnes & Cooper's chance-constrained programming)Charnes, A. and Cooper, W. W.
TüüpStochastic multi-goal optimizationMathematical programming / multi-criteria optimization
AlgallikasContini, 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
RööpnimetusedSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal ProgrammingMOGP, Multi-goal programming, Vector goal programming, Multi-criteria goal programming
Seotud64
KokkuvõteStochastic 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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ScholarGateVõrdle meetodeid: Stochastic Goal Programming · Multi-objective goal programming. Loetud 2026-06-15 aadressilt https://scholargate.app/et/compare