bi-objective optimization method and application of mechanism design based on pigs' payoff game behavior

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ID: 159060
2012
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Abstract
It takes two design goals as different game players and design variables are divided into strategy spaces owned by corresponding game player by calculating the impact factor and fuzzy clustering. By the analysis of behavior characteristics of two kinds of intelligent pigs, the big pig's behavior is cooperative and collective, but the small pig's behavior is noncooperative, which are endowed with corresponding game player. Two game players establish the mapping relationship between game players payoff functions and objective functions. In their own strategy space, each game player takes their payoff function as monoobjective for optimization. It gives the best strategy upon other players. All the best strategies are combined to be a game strategy set. With convergence and multiround game, the final game solution is obtained. Taking bi-objective optimization of luffing mechanism of compensative shave block, for example, the results show that the method can effectively solve bi-objective optimization problems with preferred target and the efficiency and accuracy are also well.
Reference Key
wang2012mathematicalbi-objective Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Lu Wang;Jian-gang Wang;Rui Meng;Neng-gang Xie
Journal journal of power sources
Year 2012
DOI
10.1155/2012/808161
URL
http://dx.doi.org/10.1155/2012/808161
Keywords
civil engineering (general)mathematics engineering (general)

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