{"title":"Multi-objective evolutionary decision support for design-supplier-manufacturing planning","authors":"F. Xue, A. Sanderson, R. Graves","doi":"10.1109/COASE.2005.1506768","DOIUrl":null,"url":null,"abstract":"Modern enterprises utilize strategic and dynamic partnerships among designers, suppliers, contract manufacturers and customers to achieve efficiency and response to rapidly changing markets. There is a clear need for planning and decision support tools, and the availability of efficient and accurate multi-objective algorithms is critical to this field. This paper poses the distributed product development as a multi-objective assignment problem, and describes a new class of multi-objective optimization algorithms based on the principles of differential evolution. The multi-objective differential evolution (MODE) algorithm is shown to approach Pareto optimal solutions in a wide class of continuous and discrete problems, providing a practical tool for this domain. A case study of real product designs from the printed circuit board industry demonstrates the effectiveness of the discrete MODE algorithm and its potential value in a decision support system for complex product development.","PeriodicalId":181408,"journal":{"name":"IEEE International Conference on Automation Science and Engineering, 2005.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Automation Science and Engineering, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2005.1506768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Modern enterprises utilize strategic and dynamic partnerships among designers, suppliers, contract manufacturers and customers to achieve efficiency and response to rapidly changing markets. There is a clear need for planning and decision support tools, and the availability of efficient and accurate multi-objective algorithms is critical to this field. This paper poses the distributed product development as a multi-objective assignment problem, and describes a new class of multi-objective optimization algorithms based on the principles of differential evolution. The multi-objective differential evolution (MODE) algorithm is shown to approach Pareto optimal solutions in a wide class of continuous and discrete problems, providing a practical tool for this domain. A case study of real product designs from the printed circuit board industry demonstrates the effectiveness of the discrete MODE algorithm and its potential value in a decision support system for complex product development.