Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Multi-Objective Ant Colony Optimization (MOACO)× | Vícecílový Genetický Algoritmus (MOGA)× | |
|---|---|---|
| Obor | Simulace | Simulace |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 1999 | 1984 |
| Tvůrce≠ | Gambardella, Taillard & Agazzi; Dorigo & Stützle | Schaffer, J. D. (early MOGA); Goldberg, D. E. (GA foundations) |
| Typ≠ | Population-based metaheuristic | Population-based evolutionary optimizer |
| Původní zdroj≠ | Gambardella, L. M., Taillard, E., & Agazzi, G. (1999). MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In D. Corne, M. Dorigo, & F. Glover (Eds.), New Ideas in Optimization (pp. 63–76). McGraw-Hill. link ↗ | Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Addison-Wesley. ISBN: 9780201157673 |
| Další názvy | MOACO, Multi-Objective ACO, Pareto Ant Colony Optimization, Multi-objective ACO | MOGA, Multi-objective GA, Evolutionary multi-objective optimization, EMO |
| Příbuzné | 4 | 4 |
| Shrnutí≠ | Multi-Objective Ant Colony Optimization (MOACO) is a swarm-intelligence metaheuristic that extends the classic Ant Colony Optimization framework to simultaneously optimize two or more conflicting objectives. Artificial ants construct candidate solutions guided by pheromone trails and heuristic information, progressively building an archive of Pareto-optimal solutions rather than converging to a single best answer. | A Multi-Objective Genetic Algorithm (MOGA) is an evolutionary computation method that evolves a population of candidate solutions toward a Pareto-optimal front, simultaneously optimizing two or more conflicting objective functions. It avoids collapsing trade-offs into a single score, instead producing a set of non-dominated solutions for the decision-maker to choose among. |
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