{"title":"基于p-中位数的设施分配自定义遗传算法","authors":"Sergio D. de S. Silva, M. Costa, C. Filho","doi":"10.15439/2019F158","DOIUrl":null,"url":null,"abstract":"The p-median problem is classified as a NP-hard problem, which demands a long time for solution. To increase the use of the method in public management, commercial, military and industrial applications, several heuristic methods has been proposed in literature. In this work, we propose a customized Genetic Algorithm for solving the p-median problem, and we present its evaluation using benchmark problems of OR-library. The customized method combines parameters used in previous studies and introduces the evolution of solutions in stationary mode for solving PMP problems. The proposed Genetic Algorithm found the optimum solution in 37 of 40 instances of p-median problem. The mean deviation from the optimal solution was 0.002% and the mean processing time using CPU core i7 was 17.7s.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Customized Genetic Algorithm for Facility Allocation using p-median\",\"authors\":\"Sergio D. de S. Silva, M. Costa, C. Filho\",\"doi\":\"10.15439/2019F158\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The p-median problem is classified as a NP-hard problem, which demands a long time for solution. To increase the use of the method in public management, commercial, military and industrial applications, several heuristic methods has been proposed in literature. In this work, we propose a customized Genetic Algorithm for solving the p-median problem, and we present its evaluation using benchmark problems of OR-library. The customized method combines parameters used in previous studies and introduces the evolution of solutions in stationary mode for solving PMP problems. The proposed Genetic Algorithm found the optimum solution in 37 of 40 instances of p-median problem. The mean deviation from the optimal solution was 0.002% and the mean processing time using CPU core i7 was 17.7s.\",\"PeriodicalId\":168208,\"journal\":{\"name\":\"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15439/2019F158\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15439/2019F158","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Customized Genetic Algorithm for Facility Allocation using p-median
The p-median problem is classified as a NP-hard problem, which demands a long time for solution. To increase the use of the method in public management, commercial, military and industrial applications, several heuristic methods has been proposed in literature. In this work, we propose a customized Genetic Algorithm for solving the p-median problem, and we present its evaluation using benchmark problems of OR-library. The customized method combines parameters used in previous studies and introduces the evolution of solutions in stationary mode for solving PMP problems. The proposed Genetic Algorithm found the optimum solution in 37 of 40 instances of p-median problem. The mean deviation from the optimal solution was 0.002% and the mean processing time using CPU core i7 was 17.7s.