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Erschienen in: Structural and Multidisciplinary Optimization 2/2013

01.02.2013 | Research Paper

Multi-objective design method based on evolution game and its application for suspension

verfasst von: Neng-Gang Xie, Rui Meng, Ye Ye, Lu Wang, Yu-Wan Cen

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 2/2013

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Abstract

Through research and bionics of biology survival mode, game players with competition, cooperation and self-adaptation capacity are introduced in the multi-objective design. The dynamic behavior and bounded rationality in game processes for players are considered according to Chinese saying “In success, commit oneself to the welfare of the society; in distress, maintain one’s own integrity”. An evolution rule, Poor-Competition-Rich-Cooperation (short for PCRC), is proposed. Then, the corresponding payoff functions of competition and cooperation behavior are established and a multi-objective design method based on evolution game is proposed. The calculation steps are as follows: 1) Taking the design objectives as different game players, and calculating factors of the design variables to objective and fuzzy clustering. The design variables are divided into multiple strategy subsets owned by each game player. 2) According to the evolution rule, each player determines its behavior and payoff function in this game round. 3) In their own strategy subsets, each game player takes their payoff as mono-objective for optimization. It gives the best strategy upon other players. And so the best strategies of all players conform the group strategy in this round. The final equilibrium solution is obtained through multi-round game based on convergence criterion. The validity and reliability of this method are shown by the results of an example of a tri-objective optimization design of passive suspension parameters.

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Metadaten
Titel
Multi-objective design method based on evolution game and its application for suspension
verfasst von
Neng-Gang Xie
Rui Meng
Ye Ye
Lu Wang
Yu-Wan Cen
Publikationsdatum
01.02.2013
Verlag
Springer-Verlag
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 2/2013
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-012-0815-3

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