{"title":"Selecting warehouse location by means of the balancing and ranking method with an interval approach","authors":"Behnam Malmir, Rahim Moein, S. K. Chaharsooghi","doi":"10.1109/IEOM.2015.7093911","DOIUrl":null,"url":null,"abstract":"Selecting the proper warehouse location has been always one of the most important and strategic challenges in the optimization process of a logistics system. Such decisions have a great importance for companies because they are costly and difficult to reverse, and entail a long term commitment. Many quantitative and qualitative factors affect the selection of the warehouse location as a long term decision. A new balancing and ranking method combined with an interval data approach has been presented in this paper for solving a warehouse location selection problem. This method involves a three-step procedure to derive an overall complete final order of the warehouses which are already selected for the decision making. The procedure involves the definition of an outranking matrix based on the criteria values for all the available warehouse locations while taking into account the frequency of superiority of one location over others. The ordering of the warehouse locations has been performed based on the information of an advantages-disadvantages table, the distance travelled after final balancing, and the provisional order of locations. This is referred to as the triangularisation. It should be noted that unlike other MCDM models, the proposed method does not require weights for the decision making criteria. In addition, the proposed approach is much more flexible than the conventional methods in some other aspects. To demonstrate the procedural implementation of the proposed method and illustrate its effectiveness, it was applied to a case study and the results are evaluated and verified.","PeriodicalId":410110,"journal":{"name":"2015 International Conference on Industrial Engineering and Operations Management (IEOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Industrial Engineering and Operations Management (IEOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEOM.2015.7093911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Selecting the proper warehouse location has been always one of the most important and strategic challenges in the optimization process of a logistics system. Such decisions have a great importance for companies because they are costly and difficult to reverse, and entail a long term commitment. Many quantitative and qualitative factors affect the selection of the warehouse location as a long term decision. A new balancing and ranking method combined with an interval data approach has been presented in this paper for solving a warehouse location selection problem. This method involves a three-step procedure to derive an overall complete final order of the warehouses which are already selected for the decision making. The procedure involves the definition of an outranking matrix based on the criteria values for all the available warehouse locations while taking into account the frequency of superiority of one location over others. The ordering of the warehouse locations has been performed based on the information of an advantages-disadvantages table, the distance travelled after final balancing, and the provisional order of locations. This is referred to as the triangularisation. It should be noted that unlike other MCDM models, the proposed method does not require weights for the decision making criteria. In addition, the proposed approach is much more flexible than the conventional methods in some other aspects. To demonstrate the procedural implementation of the proposed method and illustrate its effectiveness, it was applied to a case study and the results are evaluated and verified.