Benchmarking of product recovery alternatives in reverse logistics

Purpose – Selection of best product recovery alternative in reverse logistics (RL) has gained great attention in supply chain community. The purpose of this paper is to provide a robust group decision-making tool to select the best product recovery alternative. Design/methodology/approach – In this paper, fuzzy values, assigned to various criteria and alternatives by a number of decision makers, are converted into crisp values and then aggregated scores are evaluated. After obtaining experts’ scores, objective and subjective weights of the criteria have been calculated using variance method and analytic hierarchy process, respectively. Then integrated weights of criteria are evaluated using different proportions of the two weights. The superiority and inferiority ranking (SIR) method is then employed to achieve the final ranking of alternatives. An example is presented to demonstrate the methodology. Findings – The proposed methodology provides decision makers a systematic, flexible and realistic approach...

[1]  Ying-Ming Wang,et al.  Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment , 2006, Expert Syst. Appl..

[2]  Kwok Hung Lau,et al.  Reverse logistics in the electronic industry of China: a case study , 2009 .

[3]  Xiangru Meng,et al.  Remanufacturing Network Analysis of Third-Party Reverse Logistics for Waste Household Appliances , 2010, 2010 International Conference on Management and Service Science.

[4]  M. B. Parappagoudar,et al.  A novel multi-criteria decision making approach for selection of reverse manufacturing alternative , 2013 .

[5]  S. K. Sharma,et al.  Analysis of Barriers for Reverse Logistics: An Indian Perspective , 2011 .

[6]  Samir K. Srivastava,et al.  Managing product returns for reverse logistics , 2006 .

[7]  Semih Onüt,et al.  Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment. , 2008, Waste management.

[8]  Yih-Chearng Shiue,et al.  An Application of AHP and Sensitivity Analysis for Measuring the Best Strategy of Reverse Logistics: A Case Study of Photovoltaic Industry Chain , 2013 .

[9]  Thomas K. L. Tong,et al.  Multi-criteria material selections and end-of-life product strategy: Grey relational analysis approach , 2007 .

[10]  Selçuk Perçin,et al.  Evaluation of third‐party logistics (3PL) providers by using a two‐phase AHP and TOPSIS methodology , 2009 .

[11]  Marc Salomon,et al.  Strategic Issues in Product Recovery Management , 1995 .

[12]  Christopher J. Koroneos,et al.  A methodological framework for end-of-life management of electronic products , 2009 .

[13]  Ramesh Anbanandam,et al.  A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics , 2014, Expert Syst. Appl..

[14]  S. M. Sapuan,et al.  Material screening and choosing methods: A review , 2010 .

[15]  Mohamed Marzouk.  A superiority and inferiority ranking model for contractor selection , 2008 .

[16]  Yen-Chun Jim Wu,et al.  Reverse logistics in the publishing industry: China, Hong Kong, and Taiwan , 2006 .

[17]  Felix T.S. Chan,et al.  Flexible decision modeling of reverse logistics system: A value adding MCDM approach for alternative selection , 2009 .

[18]  Claude E. Shannon,et al.  A mathematical theory of communication , 1948, MOCO.

[19]  K. Maniya,et al.  A selection of material using a novel type decision-making method: Preference selection index method , 2010 .

[20]  Ronald S. Tibben-Lembke.  Life after death: reverse logistics and the product life cycle , 2002 .

[21]  Cheng Xiao-hong,et al.  Superiority and inferiority ranking method for grey stochastic multi-criteria decision-making , 2009 .

[22]  V. Ravi.  Selection of third-party reverse logistics providers for End-of-Life computers using TOPSIS-AHP based approach , 2012 .

[23]  Samir K. Srivastava,et al.  Network design for reverse logistics , 2008 .

[24]  M. Toffel.  The Growing Strategic Importance of End-of-Life Product Management , 2003, IEEE Engineering Management Review.

[25]  Chwen Sheu,et al.  A model for reverse logistics entry by third-party providers , 2002 .

[26]  Xiaozhan Xu,et al.  The SIR method: A superiority and inferiority ranking method for multiple criteria decision making , 2001, Eur. J. Oper. Res..

[27]  Jamal Shahrabi,et al.  PROJECT SELECTION BY USING FUZZY AHP AND TOPSIS TECHNIQUE , 2007 .

[28]  George Tagaras,et al.  Drivers and obstacles of product recovery activities in the Greek industry , 2011 .

[29]  Ajoy Kumar Dey,et al.  An analytical approach for selection of a logistics provider , 2010 .

[30]  R. Rao,et al.  Vendor selection in a supply chain using analytic hierarchy process and genetic algorithm methods , 2007 .

[31]  Jean Pierre Brans,et al.  HOW TO SELECT AND HOW TO RANK PROJECTS: THE PROMETHEE METHOD , 1986 .

[32]  Clifford Chan,et al.  Selection of solar energy for green building using superiority and inferiority multi-criteria ranking (SIR) method , 2011 .

[33]  Shan-Huo Chen.  Ranking fuzzy numbers with maximizing set and minimizing set , 1985 .

[34]  Bernard Roy,et al.  Multicriteria programming of water supply systems for rural areas , 1992 .

[35]  Z. Yue.  A method for group decision-making based on determining weights of decision makers using TOPSIS , 2011 .

[36]  Min Wu,et al.  Topsis-AHP simulation model and its application to supply chain management , 2007 .

[37]  Chi Ming Tam,et al.  Locating large‐scale harbour‐front project developments using SIR method with grey aggregation approach , 2008 .

[38]  Ronald S. Tibben-Lembke,et al.  Going Backwards: Reverse Logistics Trends and Practices , 1999 .

[39]  Askiner Gungor,et al.  Issues in environmentally conscious manufacturing and product recovery: a survey , 1999 .

[40]  Osama Moselhi,et al.  Measuring sensitivity of Procurement Decisions using superiority and Inferiority Ranking , 2013, Int. J. Inf. Technol. Decis. Mak..

[41]  Mehmet Ali Ilgin,et al.  Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art. , 2010, Journal of environmental management.

[42]  Abbas Rashidi,et al.  Selection of Project Managers in Construction Firm s Using Analytic Hierarchy Process (AHP) and Fuzzy Topsis: A Case Study , 2011 .

[43]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[44]  Marisa P. de Brito,et al.  A reverse logistics diagnostic tool: the case of the consumer electronics industry , 2010 .

[45]  Y. W. Wong,et al.  Selection of concrete pump using the Superiority and Inferiority Ranking method , 2004 .

[46]  Belarmino Adenso-Díaz,et al.  Environmental and reverse logistics policies in European bottling and packaging firms , 2004 .

[47]  R. Venkata Rao,et al.  Industrial robot selection using a novel decision making method considering objective and subjective preferences , 2011, Robotics Auton. Syst..

[48]  Hark Hwang,et al.  An optimal ordering and recovery policy for reusable items , 2002 .

[49]  Hilmi Yuksel.  An Analytical Hierarchy Process decision model for e-waste collection center location selection , 2009, 2009 International Conference on Computers & Industrial Engineering.

[50]  Zelda B. Zabinsky,et al.  A multicriteria decision making model for reverse logistics using analytical hierarchy process , 2011 .

[51]  Jiuh-Biing Sheu,et al.  Green supply chain management, reverse logistics and nuclear power generation , 2008 .

[52]  S. M. Sapuan,et al.  Material selection based on ordinal data , 2010 .