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| Многокритериално линейно програмиране (МКЛП)× | Программиране с целеви стойности (Goal Programming)× | Многоцелева оптимизация× | |
|---|---|---|---|
| Област≠ | Симулационно моделиране | Вземане на решения | Симулационно моделиране |
| Семейство≠ | Process / pipeline | MCDM | Process / pipeline |
| Година на възникване≠ | 1955–1986 | 1955 | 1896 (concept); 1989–2002 (evolutionary algorithms era) |
| Създател≠ | Steuer, R. E.; Charnes, A.; Cooper, W. W. | Charnes, A., Cooper, W. W. | Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al. |
| Тип≠ | Mathematical optimization / vector optimization | Multi-objective optimisation — weighted/lexicographic goal deviation minimisation | Optimization framework |
| Основополагащ източник≠ | Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York. ISBN: 9780471888468 | Charnes, 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 |
| Други названия≠ | MOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization | — | MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization |
| Свързани≠ | 3 | 8 | 3 |
| Резюме≠ | Multi-Objective Linear Programming (MOLP) extends classical linear programming to handle several conflicting linear objective functions simultaneously over a feasible region defined by linear constraints. Instead of a single optimal solution, MOLP produces a Pareto-efficient frontier from which a decision-maker selects a preferred trade-off. It is foundational to operations research and management science for resource allocation, planning, and design problems with competing goals. | 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. | 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. |
| ScholarGateНабор от данни ↗ |
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