{"title":"基于随机响应技术的软计算优化模型","authors":"T. A. Tarray, Z. A. Ganie","doi":"10.1109/PIECON56912.2023.10085835","DOIUrl":null,"url":null,"abstract":"We explore a randomized response model in a two stage stratified random sampling model and try to minimize the variance while taking costs into consideration using the existing optimization model as a guide. Applying the alpha-cut method’s optimal allocation strategy at the specified alpha value solves the problem. Additionally provided as support for the current study are numerical examples.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"7 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An optimization model using soft computing with the randomised response technique\",\"authors\":\"T. A. Tarray, Z. A. Ganie\",\"doi\":\"10.1109/PIECON56912.2023.10085835\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We explore a randomized response model in a two stage stratified random sampling model and try to minimize the variance while taking costs into consideration using the existing optimization model as a guide. Applying the alpha-cut method’s optimal allocation strategy at the specified alpha value solves the problem. Additionally provided as support for the current study are numerical examples.\",\"PeriodicalId\":182428,\"journal\":{\"name\":\"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)\",\"volume\":\"7 5\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIECON56912.2023.10085835\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIECON56912.2023.10085835","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An optimization model using soft computing with the randomised response technique
We explore a randomized response model in a two stage stratified random sampling model and try to minimize the variance while taking costs into consideration using the existing optimization model as a guide. Applying the alpha-cut method’s optimal allocation strategy at the specified alpha value solves the problem. Additionally provided as support for the current study are numerical examples.