{"title":"解密不确定偏好下 CoCoSo 排序方法的稳定性和性能问题","authors":"Sundararajan Dhruva, Raghunathan Krishankumar, Dragan Pamucar, Edmundas Kazimieras Zavadskas, Kattur Soundarapandian Ravichandran","doi":"10.15388/24-infor565","DOIUrl":null,"url":null,"abstract":"This paper attempts to demystify the stability of CoCoSo ranking method via a comprehensive simulation experiment. In the experiment, matrices of different dimensions are generated via Python with fuzzy data. Stability is investigated via adequacy and partial adequacy tests. The test passes if the ranking order does not change even after changes are made to entities, and the partial pass signifies that the top ranked alternative remains intact. Results infer that CoCoSo method has better stability with respect to change of alternatives compared to criteria; and CoCoSo method shows better stability with respect to partial adequacy test for criteria.\nPDF XML","PeriodicalId":56292,"journal":{"name":"Informatica","volume":"15 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Demystifying the Stability and the Performance Aspects of CoCoSo Ranking Method under Uncertain Preferences\",\"authors\":\"Sundararajan Dhruva, Raghunathan Krishankumar, Dragan Pamucar, Edmundas Kazimieras Zavadskas, Kattur Soundarapandian Ravichandran\",\"doi\":\"10.15388/24-infor565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper attempts to demystify the stability of CoCoSo ranking method via a comprehensive simulation experiment. In the experiment, matrices of different dimensions are generated via Python with fuzzy data. Stability is investigated via adequacy and partial adequacy tests. The test passes if the ranking order does not change even after changes are made to entities, and the partial pass signifies that the top ranked alternative remains intact. Results infer that CoCoSo method has better stability with respect to change of alternatives compared to criteria; and CoCoSo method shows better stability with respect to partial adequacy test for criteria.\\nPDF XML\",\"PeriodicalId\":56292,\"journal\":{\"name\":\"Informatica\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Informatica\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.15388/24-infor565\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informatica","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.15388/24-infor565","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
摘要
本文试图通过一个综合模拟实验来揭开 CoCoSo 排序方法稳定性的神秘面纱。在实验中,不同维度的矩阵通过 Python 生成模糊数据。稳定性通过充分性和部分充分性测试进行研究。如果即使对实体进行了更改,排名顺序也不会发生变化,则测试通过;如果排名靠前的备选方案保持不变,则部分通过。结果推断,与标准相比,CoCoSo 方法在备选方案发生变化时具有更好的稳定性;与标准的部分充分性测试相比,CoCoSo 方法显示出更好的稳定性。PDF XML
Demystifying the Stability and the Performance Aspects of CoCoSo Ranking Method under Uncertain Preferences
This paper attempts to demystify the stability of CoCoSo ranking method via a comprehensive simulation experiment. In the experiment, matrices of different dimensions are generated via Python with fuzzy data. Stability is investigated via adequacy and partial adequacy tests. The test passes if the ranking order does not change even after changes are made to entities, and the partial pass signifies that the top ranked alternative remains intact. Results infer that CoCoSo method has better stability with respect to change of alternatives compared to criteria; and CoCoSo method shows better stability with respect to partial adequacy test for criteria.
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期刊介绍:
The quarterly journal Informatica provides an international forum for high-quality original research and publishes papers on mathematical simulation and optimization, recognition and control, programming theory and systems, automation systems and elements. Informatica provides a multidisciplinary forum for scientists and engineers involved in research and design including experts who implement and manage information systems applications.