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תכנות מטרות (Goal Programming)×אופטימיזציה רב-מטרתית×
תחוםקבלת החלטותסימולציה
משפחהMCDMProcess / pipeline
שנת המקור19551896 (concept); 1989–2002 (evolutionary algorithms era)
הוגה השיטהCharnes, A., Cooper, W. W.Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al.
סוגMulti-objective optimisation — weighted/lexicographic goal deviation minimisationOptimization framework
מקור מכונןCharnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science DOI ↗Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396
כינוייםMOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization
קשורות83
תקצירGOAL-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.Multi-Objective Optimization (MOO) is a mathematical and computational framework for finding solutions that simultaneously optimize two or more conflicting objective functions. Rather than collapsing all goals into a single scalar, MOO produces a set of trade-off solutions — the Pareto front — from which a decision-maker selects according to preference. It is widely used in engineering design, operations research, logistics, economics, and policy analysis.
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ScholarGateהשוואת שיטות: GOAL-PROGRAMMING · Multi-Objective Optimization. אוחזר בתאריך 2026-06-15 מתוך https://scholargate.app/he/compare