|
| << vorige | volgende >> |
Tijdschrift beschrijving
Alle jaargangen van het bijbehorende tijdschrift
Alle afleveringen van het bijbehorende jaargang
Alle artikelen van de bijbehorende aflevering
Details van artikel 8 van 9 gevonden artikelen
| Titel: |
PARETO OPTIMIZATION USING THE STRUGGLE GENETIC CROWDING ALGORITHM |
| Auteur: |
Andersson, Johan Wallace, David |
| Verschenen in: |
Engineering optimization |
| Paginering: | Jaargang 34 (2002) nr. 6 pagina's 623-643 |
| Jaar: |
2002 |
| Inhoud: |
Many real-world engineering design problems involve the simultaneous optimization of several conflicting objectives. In this paper, a method combining the struggle genetic crowding algorithm with Pareto-based population ranking is proposed to elicit trade-off frontiers. The new method has been tested on a variety of published problems, reliably locating both discontinuous Pareto frontiers as well as multiple Pareto frontiers in multi-modal search spaces. Other published multi-objective genetic algorithms are less robust in locating both global and local Pareto frontiers in a single optimization. For example, in a multi-modal test problem a previously published non-dominated sorting GA (NSGA) located the global Pareto frontier in 41% of the optimizations, while the proposed method located both global and local frontiers in all test runs. Additionally, the algorithm requires little problem specific tuning of parameters. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 8 van 9 gevonden artikelen
| << vorige | volgende >> |