{"title":"Multi-Attribute Decision Making using Competitive Neural Networks","authors":"M. Abdoos","doi":"10.1109/ICCKE50421.2020.9303699","DOIUrl":null,"url":null,"abstract":"Multi Attribute Decision Making (MADM) methods are widely used for making the optimal decision. Different approaches have been presented to solve decision-making problems. The aim of MADM is ranking of feasible alternatives. In this paper, a new approach to solve MADM problems using an artificial neural network has been presented. The competition among alternatives is modeled by a competitive network. The ordered list of the alternatives is achieved in two phases: partial ranking and fine ranking. The results of this approach are compared with Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS).","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCKE50421.2020.9303699","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Multi Attribute Decision Making (MADM) methods are widely used for making the optimal decision. Different approaches have been presented to solve decision-making problems. The aim of MADM is ranking of feasible alternatives. In this paper, a new approach to solve MADM problems using an artificial neural network has been presented. The competition among alternatives is modeled by a competitive network. The ordered list of the alternatives is achieved in two phases: partial ranking and fine ranking. The results of this approach are compared with Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS).