{"title":"A Linear Physical Programming Approach for Evaluating Collection Centers for End-of-Life Products","authors":"Bandar A. Alkhayyal, S. Gupta","doi":"10.1108/S0276-897620180000019005","DOIUrl":null,"url":null,"abstract":"Abstract \nThis chapter studies the integration of quantitative and qualitative attributes of a particular issue in the strategic “designing” level of the reverse supply chain (RSC) process in a multicriteria decision-making environment. The study employs an analytical network process (ANP) to determine the performance indices of the collection centers derived through qualitative criteria from the remanufacturing facilities that are interested in buying used products. The evaluating criteria are comprised as a four-level hierarchy: the first level contains the objective of evaluating the collection centers, the second level involves the main evaluation criteria taken from the perspective of a remanufacturing facility, the third level contains the subcriteria under the main evaluation criteria, and the fourth level has the collection centers. ANP is presented herein as a matrix that comprises a list of all facets listed horizontally and vertically. This particular method is of value when key elements of a decision are difficult to quantify and contrast, and thus the identification of important facets and their incorporation into a linear physical programing (LPP) environment is of value. To determine the quality of end-of-life (EOL) products for transport from collection centers to remanufacturing facilities, a physical programming approach is adopted. Four criteria and their satisfaction are focused upon: (1) maximizing the total value of purchase; (2) minimizing the total cost of transportation; (3) minimizing the disposal cost; and (4) minimizing the purchase cost. A numerical example is considered in which three collection center locations are evaluated to identify the optimal collection center.","PeriodicalId":244858,"journal":{"name":"Applications of Management Science","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applications of Management Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/S0276-897620180000019005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Abstract
This chapter studies the integration of quantitative and qualitative attributes of a particular issue in the strategic “designing” level of the reverse supply chain (RSC) process in a multicriteria decision-making environment. The study employs an analytical network process (ANP) to determine the performance indices of the collection centers derived through qualitative criteria from the remanufacturing facilities that are interested in buying used products. The evaluating criteria are comprised as a four-level hierarchy: the first level contains the objective of evaluating the collection centers, the second level involves the main evaluation criteria taken from the perspective of a remanufacturing facility, the third level contains the subcriteria under the main evaluation criteria, and the fourth level has the collection centers. ANP is presented herein as a matrix that comprises a list of all facets listed horizontally and vertically. This particular method is of value when key elements of a decision are difficult to quantify and contrast, and thus the identification of important facets and their incorporation into a linear physical programing (LPP) environment is of value. To determine the quality of end-of-life (EOL) products for transport from collection centers to remanufacturing facilities, a physical programming approach is adopted. Four criteria and their satisfaction are focused upon: (1) maximizing the total value of purchase; (2) minimizing the total cost of transportation; (3) minimizing the disposal cost; and (4) minimizing the purchase cost. A numerical example is considered in which three collection center locations are evaluated to identify the optimal collection center.