Sadeque Hamdan, R. Larbi, Ali Cheaitou, I. Alsyouf
{"title":"绿色旅游购买者问题模型:双目标优化方法","authors":"Sadeque Hamdan, R. Larbi, Ali Cheaitou, I. Alsyouf","doi":"10.1109/ICMSAO.2017.7934841","DOIUrl":null,"url":null,"abstract":"The green traveling purchaser problem (GTPP) is a generalization of the Traveling Purchaser Problem which consists of selecting suppliers, allocating orders and choosing the best routes, while minimizing the purchasing and traveling costs and CO2 emissions. The two objective functions pertaining to minimization of CO2 emissions and purchasing costs are in some cases conflicting and are thus considered separately. This paper presents an exact method to solve the proposed bi-objective optimization model where the bi-objective mathematical model is transformed into a single objective function model using the weighted comprehensive criterion method. The model is solved using branch and cut algorithm in MATLAB software. Computational experiments were carried out using two random instances, and the results show that the algorithm gives the bi-objective Pareto optimal solutions with significant difference in computation times when the speed is constant or varies between the routes. Using different weighting factors, this model can be considered as a decision making tool that allows decision makers to use the solution that fits the most with their organization's strategy.","PeriodicalId":265345,"journal":{"name":"2017 7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Green Traveling Purchaser Problem model: A bi-objective optimization approach\",\"authors\":\"Sadeque Hamdan, R. Larbi, Ali Cheaitou, I. Alsyouf\",\"doi\":\"10.1109/ICMSAO.2017.7934841\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The green traveling purchaser problem (GTPP) is a generalization of the Traveling Purchaser Problem which consists of selecting suppliers, allocating orders and choosing the best routes, while minimizing the purchasing and traveling costs and CO2 emissions. The two objective functions pertaining to minimization of CO2 emissions and purchasing costs are in some cases conflicting and are thus considered separately. This paper presents an exact method to solve the proposed bi-objective optimization model where the bi-objective mathematical model is transformed into a single objective function model using the weighted comprehensive criterion method. The model is solved using branch and cut algorithm in MATLAB software. Computational experiments were carried out using two random instances, and the results show that the algorithm gives the bi-objective Pareto optimal solutions with significant difference in computation times when the speed is constant or varies between the routes. Using different weighting factors, this model can be considered as a decision making tool that allows decision makers to use the solution that fits the most with their organization's strategy.\",\"PeriodicalId\":265345,\"journal\":{\"name\":\"2017 7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMSAO.2017.7934841\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSAO.2017.7934841","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Green Traveling Purchaser Problem model: A bi-objective optimization approach
The green traveling purchaser problem (GTPP) is a generalization of the Traveling Purchaser Problem which consists of selecting suppliers, allocating orders and choosing the best routes, while minimizing the purchasing and traveling costs and CO2 emissions. The two objective functions pertaining to minimization of CO2 emissions and purchasing costs are in some cases conflicting and are thus considered separately. This paper presents an exact method to solve the proposed bi-objective optimization model where the bi-objective mathematical model is transformed into a single objective function model using the weighted comprehensive criterion method. The model is solved using branch and cut algorithm in MATLAB software. Computational experiments were carried out using two random instances, and the results show that the algorithm gives the bi-objective Pareto optimal solutions with significant difference in computation times when the speed is constant or varies between the routes. Using different weighting factors, this model can be considered as a decision making tool that allows decision makers to use the solution that fits the most with their organization's strategy.