N. Nayak, Prasanna K., S. Datta, S. Mahapatra, S. Sahu
{"title":"一种新的虚拟企业合作伙伴选择的群优化技术","authors":"N. Nayak, Prasanna K., S. Datta, S. Mahapatra, S. Sahu","doi":"10.1109/IEEM.2010.5674316","DOIUrl":null,"url":null,"abstract":"Partner selection is a critical issue in formation of virtual enterprises and increasing its operational effectiveness. Such a problem belongs to combinatorial optimization category and known as NP-hard problem. Usually, evolutionary methods are being adopted to obtain near-optimal solutions. In this paper, a variant of swarm optimization is proposed to handle combinatorial problems efficiently compared to its continuous counterpart. The method substantially reduces the number of tuning parameters in the algorithm. The algorithm presented include main crucial factors for partner selection such as the running cost, reaction time and running risk and select the partners for various processes that minimizes total cost. The working of the algorithm is demonstrated with the help of a typical example. Exhaustive simulation illustrates the effectiveness of algorithm.","PeriodicalId":285694,"journal":{"name":"2010 IEEE International Conference on Industrial Engineering and Engineering Management","volume":"243-249 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A novel swarm optimization technique for partner selection in virtual enterprise\",\"authors\":\"N. Nayak, Prasanna K., S. Datta, S. Mahapatra, S. Sahu\",\"doi\":\"10.1109/IEEM.2010.5674316\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Partner selection is a critical issue in formation of virtual enterprises and increasing its operational effectiveness. Such a problem belongs to combinatorial optimization category and known as NP-hard problem. Usually, evolutionary methods are being adopted to obtain near-optimal solutions. In this paper, a variant of swarm optimization is proposed to handle combinatorial problems efficiently compared to its continuous counterpart. The method substantially reduces the number of tuning parameters in the algorithm. The algorithm presented include main crucial factors for partner selection such as the running cost, reaction time and running risk and select the partners for various processes that minimizes total cost. The working of the algorithm is demonstrated with the help of a typical example. Exhaustive simulation illustrates the effectiveness of algorithm.\",\"PeriodicalId\":285694,\"journal\":{\"name\":\"2010 IEEE International Conference on Industrial Engineering and Engineering Management\",\"volume\":\"243-249 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Industrial Engineering and Engineering Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM.2010.5674316\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Industrial Engineering and Engineering Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2010.5674316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel swarm optimization technique for partner selection in virtual enterprise
Partner selection is a critical issue in formation of virtual enterprises and increasing its operational effectiveness. Such a problem belongs to combinatorial optimization category and known as NP-hard problem. Usually, evolutionary methods are being adopted to obtain near-optimal solutions. In this paper, a variant of swarm optimization is proposed to handle combinatorial problems efficiently compared to its continuous counterpart. The method substantially reduces the number of tuning parameters in the algorithm. The algorithm presented include main crucial factors for partner selection such as the running cost, reaction time and running risk and select the partners for various processes that minimizes total cost. The working of the algorithm is demonstrated with the help of a typical example. Exhaustive simulation illustrates the effectiveness of algorithm.