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確率的目標計画法×Multi-Objective Goal Programming×
分野シミュレーションシミュレーション
系統Process / pipelineProcess / pipeline
提唱年19681961
提唱者Contini, B. (building on Charnes & Cooper's chance-constrained programming)Charnes, A. and Cooper, W. W.
種類Stochastic multi-goal optimizationMathematical programming / multi-criteria optimization
原典Contini, 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
別名SGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal ProgrammingMOGP, Multi-goal programming, Vector goal programming, Multi-criteria goal programming
関連64
概要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.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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ScholarGate手法を比較: Stochastic Goal Programming · Multi-objective goal programming. 2026-06-15に以下より取得 https://scholargate.app/ja/compare