{"title":"基于遗传蝙蝠算法的多目标选择性拆卸序列规划","authors":"Zhi Gang Xu","doi":"10.4028/p-pw66ig","DOIUrl":null,"url":null,"abstract":"The genetic bat algorithm is being actively investigated for its application in the complex multi-objective product selective disassembly sequence planning problem. To broaden the scope of the search space and enhance the overall search efficiency, the traditional bat algorithm has undergone discretization, incorporating a cross-mutation mechanism into the construction of the fitness function model. To assess the efficacy of this novel approach, an industrial mechanical arm is utilized as a representative case study. Upon comparison with the traditional bat algorithm, the proposed method exhibits shorter convergence times across a range of population sizes, thus validating its effectiveness.","PeriodicalId":512976,"journal":{"name":"Engineering Headway","volume":"32 17","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genetic Bat Algorithm-Based Multi-Objective Selective Disassembly Sequence Planning\",\"authors\":\"Zhi Gang Xu\",\"doi\":\"10.4028/p-pw66ig\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The genetic bat algorithm is being actively investigated for its application in the complex multi-objective product selective disassembly sequence planning problem. To broaden the scope of the search space and enhance the overall search efficiency, the traditional bat algorithm has undergone discretization, incorporating a cross-mutation mechanism into the construction of the fitness function model. To assess the efficacy of this novel approach, an industrial mechanical arm is utilized as a representative case study. Upon comparison with the traditional bat algorithm, the proposed method exhibits shorter convergence times across a range of population sizes, thus validating its effectiveness.\",\"PeriodicalId\":512976,\"journal\":{\"name\":\"Engineering Headway\",\"volume\":\"32 17\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Headway\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4028/p-pw66ig\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Headway","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4028/p-pw66ig","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetic Bat Algorithm-Based Multi-Objective Selective Disassembly Sequence Planning
The genetic bat algorithm is being actively investigated for its application in the complex multi-objective product selective disassembly sequence planning problem. To broaden the scope of the search space and enhance the overall search efficiency, the traditional bat algorithm has undergone discretization, incorporating a cross-mutation mechanism into the construction of the fitness function model. To assess the efficacy of this novel approach, an industrial mechanical arm is utilized as a representative case study. Upon comparison with the traditional bat algorithm, the proposed method exhibits shorter convergence times across a range of population sizes, thus validating its effectiveness.