{"title":"用目标规划和相似函数求解不完全ahp模型","authors":"Maryam Bagheri, Fard Sharabiani, M. Gholamian","doi":"10.13033/ijahp.v15i1.1003","DOIUrl":null,"url":null,"abstract":"The pairwise comparison matrix (PCM) is a crucial element of the Analytic Hierarchy Process (AHP). In many cases, the PCM is incomplete and this complicates the decision-making process. Hence, the present study offers a novel approach for dealing with incomplete information in group decision-making. We present a new model of incomplete AHP using goal programming (GP) and the similarity function. The minimization of this similarity function reduces errors in decision-making. The proposed model will be able to estimate the unknown elements in the pairwise comparison matrix and calculate the weight vectors obtained from the matrices. Several examples are implemented to elaborate on the estimation of unknown elements and weight vectors in the proposed model. The results show that the unknown elements have an acceptable value with an appropriate consistency rate.","PeriodicalId":37297,"journal":{"name":"International Journal of the Analytic Hierarchy Process","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A NEW SOLUTION FOR INCOMPLETE AHP MODEL USING GOAL PROGRAMMING AND SIMILARITY FUNCTION\",\"authors\":\"Maryam Bagheri, Fard Sharabiani, M. Gholamian\",\"doi\":\"10.13033/ijahp.v15i1.1003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The pairwise comparison matrix (PCM) is a crucial element of the Analytic Hierarchy Process (AHP). In many cases, the PCM is incomplete and this complicates the decision-making process. Hence, the present study offers a novel approach for dealing with incomplete information in group decision-making. We present a new model of incomplete AHP using goal programming (GP) and the similarity function. The minimization of this similarity function reduces errors in decision-making. The proposed model will be able to estimate the unknown elements in the pairwise comparison matrix and calculate the weight vectors obtained from the matrices. Several examples are implemented to elaborate on the estimation of unknown elements and weight vectors in the proposed model. The results show that the unknown elements have an acceptable value with an appropriate consistency rate.\",\"PeriodicalId\":37297,\"journal\":{\"name\":\"International Journal of the Analytic Hierarchy Process\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of the Analytic Hierarchy Process\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13033/ijahp.v15i1.1003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of the Analytic Hierarchy Process","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13033/ijahp.v15i1.1003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Decision Sciences","Score":null,"Total":0}
A NEW SOLUTION FOR INCOMPLETE AHP MODEL USING GOAL PROGRAMMING AND SIMILARITY FUNCTION
The pairwise comparison matrix (PCM) is a crucial element of the Analytic Hierarchy Process (AHP). In many cases, the PCM is incomplete and this complicates the decision-making process. Hence, the present study offers a novel approach for dealing with incomplete information in group decision-making. We present a new model of incomplete AHP using goal programming (GP) and the similarity function. The minimization of this similarity function reduces errors in decision-making. The proposed model will be able to estimate the unknown elements in the pairwise comparison matrix and calculate the weight vectors obtained from the matrices. Several examples are implemented to elaborate on the estimation of unknown elements and weight vectors in the proposed model. The results show that the unknown elements have an acceptable value with an appropriate consistency rate.
期刊介绍：
IJAHP is a scholarly journal that publishes papers about research and applications of the Analytic Hierarchy Process(AHP) and Analytic Network Process(ANP), theories of measurement that can handle tangibles and intangibles; these methods are often applied in multicriteria decision making, prioritization, ranking and resource allocation, especially when groups of people are involved. The journal encourages research papers in both theory and applications. Empirical investigations, comparisons and exemplary real-world applications in diverse areas are particularly welcome.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
