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| Genetischer Algorithmus× | Zielprogrammierung× | |
|---|---|---|
| Fachgebiet≠ | Optimierung | Entscheidungsfindung |
| Familie≠ | Process / pipeline | MCDM |
| Entstehungsjahr≠ | 1975 | 1955 |
| Urheber≠ | John Henry Holland | Charnes, A., Cooper, W. W. |
| Typ≠ | Population-based metaheuristic | Multi-objective optimisation — weighted/lexicographic goal deviation minimisation |
| Wegweisende Quelle≠ | Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗ | Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science DOI ↗ |
| Aliasnamen≠ | GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon | — |
| Verwandt≠ | 5 | 8 |
| Zusammenfassung≠ | A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail. | 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. |
| ScholarGateDatensatz ↗ |
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