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方法族Process / pipelineMCDM
起源年份1961 (GP); 1990s (robust extension)1955
提出者Charnes, A. & Cooper, W. W. (goal programming); Mulvey, J. M. et al. (robust optimization framework)Charnes, A., Cooper, W. W.
类型Mathematical programming under uncertaintyMulti-objective optimisation — weighted/lexicographic goal deviation minimisation
开创性文献Charnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 9780471155041Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science DOI ↗
别名RGP, Goal Programming under Uncertainty, Robust GP, Uncertainty-Aware Goal Programming
相关58
摘要Robust 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.GOAL-PROGRAMMING (Goal Programming — Minimise deviations from multiple aspiration levels) is a ranking multi-criteria decision-making (MCDM) method introduced by Charnes, A., Cooper, W. W. in 1955. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGate方法对比: Robust goal programming · GOAL-PROGRAMMING. 于 2026-06-15 检索自 https://scholargate.app/zh/compare