| Chaotic migration-based pseudo parallel genetic algorithm and its application in inventory optimization |
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| 引用本文： | Chen Xiaofang,Gui Weihua & Wang YalinSchool of Information Science & Engineering,Central South University,Changsha 410083,P. R. China. Chaotic migration-based pseudo parallel genetic algorithm and its application in inventory optimization[J]. 系统工程与电子技术(英文版), 2005, 16(2) |
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| 作者姓名： | Chen Xiaofang Gui Weihua & Wang YalinSchool of Information Science & Engineering Central South University Changsha 410083 P. R. China |
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| 作者单位： | Chen Xiaofang，Gui Weihua & Wang YalinSchool of Information Science & Engineering，Central South University，Changsha 410083，P. R. China |
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| 基金项目： | ThisprojectwassupportedbytheNationalKeyBasicResearchandDevelopmentProgram(2002CB312203). |
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| 摘 要： | 1.INTRODUCTION Geneticalgorithm(GA)isacomputationmodelsimulat ingevolutionprocessofcreatures.Inspiteofitsremark ableprogress,thetroublecausedbyprematureduring evolutionhasbroughtdifficultyforGAapplications.A sortofmulti populationGAishighlyregardedformaking thebestofparallelstructureandgroupevolvementofGA witheasyimplementation[1].ButPGAhasahighrequest forhardwareenvironmentofmultiprocessorsuchlike Transputernetwork,MIMD,SIMDorLAN[2,3].For thoseoptimizationproblemsoflowerrequestf…
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Chaotic migration-based pseudo parallel genetic algorithm and its application in inventory optimization |
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| Chen Xiaofang,Gui Weihua,Wang Yalin. Chaotic migration-based pseudo parallel genetic algorithm and its application in inventory optimization[J]. Journal of Systems Engineering and Electronics, 2005, 16(2) |
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| Authors: | Chen Xiaofang Gui Weihua Wang Yalin |
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| Affiliation: | School of Information Science & Engineering, Central South University, Changsha 410083, P. R. China |
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| Abstract: | Considering premature convergence in the searching process of genetic algorithm, a chaotic migration-based pseudo parallel genetic algorithm (CMPPGA) is proposed, which applies the idea of isolated evolution and information exchanging in distributed Parallel Genetic Algorithm by serial program structure to solve optimization problem of low real-time demand. In this algorithm, asynchronic migration of individuals during parallel evolution is guided by a chaotic migration sequence. Information exchanging among sub-populations is ensured to be efficient and sufficient due to that the sequence is ergodic and stochastic. Simulation study of CMPPGA shows its strong global search ability, superiority to standard genetic algorithm and high immunity against premature convergence. According to the practice of raw material supply, an inventory programming model is set up and solved by CMPPGA with satisfactory results returned. |
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| Keywords: | parallel genetic algorithm chaos premature convergence inventory optimization. |
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