Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Goal Programming× | Otimização Multiobjetivo× | |
|---|---|---|
| Área≠ | Tomada de decisão | Simulação |
| Família≠ | MCDM | Process / pipeline |
| Ano de origem≠ | 1955 | 1896 (concept); 1989–2002 (evolutionary algorithms era) |
| Autor original≠ | Charnes, A., Cooper, W. W. | Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al. |
| Tipo≠ | Multi-objective optimisation — weighted/lexicographic goal deviation minimisation | Optimization framework |
| Fonte seminal≠ | 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 |
| Outros nomes≠ | — | MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization |
| Relacionados≠ | 8 | 3 |
| Resumo≠ | 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. |
| ScholarGateConjunto de dados ↗ |
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