Romit S. Beed, Ankita Sarkar, R. Sinha, Deboshruti Dasgupta
{"title":"用模拟退火方法研究了利润优化参数对货架空间分配问题的影响","authors":"Romit S. Beed, Ankita Sarkar, R. Sinha, Deboshruti Dasgupta","doi":"10.32010/26166127.2020.3.2.255.268","DOIUrl":null,"url":null,"abstract":"Shelf space allocation has always remained a crucial issue for any retail store, as space is a limited resource. This work proposes a model that uses a hyper-heuristic approach to allocate products on shelves to maximize the retailer's profit. This work has concentrated on providing a solution specifically for a consumer packaged goods store. There exist multiple conflicting objectives and constraints which influence the profit. The consequence is a non-linear programming model having a complex objective function, which is solved by using multiple neighborhood approaches using simulated annealing as simulated annealing is a useful tool for solving complex combinatorial optimization problems. Detailed analysis of the proposed technique of using annealing and reheating has revealed the effectiveness in profit maximization in the shelf space allocation problem. Various simulated annealing parameters have been studied in this paper, which provides optimum values for maximizing profit.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A STUDY OF THE EFFECT OF THE PARAMETERS FOR OPTIMIZING PROFIT USING SIMULATED ANNEALING TO SOLVE SHELF SPACE ALLOCATION PROBLEM\",\"authors\":\"Romit S. Beed, Ankita Sarkar, R. Sinha, Deboshruti Dasgupta\",\"doi\":\"10.32010/26166127.2020.3.2.255.268\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Shelf space allocation has always remained a crucial issue for any retail store, as space is a limited resource. This work proposes a model that uses a hyper-heuristic approach to allocate products on shelves to maximize the retailer's profit. This work has concentrated on providing a solution specifically for a consumer packaged goods store. There exist multiple conflicting objectives and constraints which influence the profit. The consequence is a non-linear programming model having a complex objective function, which is solved by using multiple neighborhood approaches using simulated annealing as simulated annealing is a useful tool for solving complex combinatorial optimization problems. Detailed analysis of the proposed technique of using annealing and reheating has revealed the effectiveness in profit maximization in the shelf space allocation problem. Various simulated annealing parameters have been studied in this paper, which provides optimum values for maximizing profit.\",\"PeriodicalId\":275688,\"journal\":{\"name\":\"Azerbaijan Journal of High Performance Computing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Azerbaijan Journal of High Performance Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32010/26166127.2020.3.2.255.268\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Azerbaijan Journal of High Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32010/26166127.2020.3.2.255.268","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A STUDY OF THE EFFECT OF THE PARAMETERS FOR OPTIMIZING PROFIT USING SIMULATED ANNEALING TO SOLVE SHELF SPACE ALLOCATION PROBLEM
Shelf space allocation has always remained a crucial issue for any retail store, as space is a limited resource. This work proposes a model that uses a hyper-heuristic approach to allocate products on shelves to maximize the retailer's profit. This work has concentrated on providing a solution specifically for a consumer packaged goods store. There exist multiple conflicting objectives and constraints which influence the profit. The consequence is a non-linear programming model having a complex objective function, which is solved by using multiple neighborhood approaches using simulated annealing as simulated annealing is a useful tool for solving complex combinatorial optimization problems. Detailed analysis of the proposed technique of using annealing and reheating has revealed the effectiveness in profit maximization in the shelf space allocation problem. Various simulated annealing parameters have been studied in this paper, which provides optimum values for maximizing profit.