A MCDM APPROACH WITH FUZZY DEMATEL AND FUZZY TOPSIS FOR 3PL PROVIDER SELECTION

Year 2014, Volume: 32 Issue: 2, 222 - 239, 01.06.2014

Özkan Bali Salih Tutun Ali Pala Cihan Çörekçi

Abstract

Especially, in the last 20 years, firms wanting to return core competencies and reduce costs are shown that they prefer outsourcing options in their logistics activities. Therefore, third party logistics (3PL) provider selection is one of the most important decision making problems for the firms that using outsourcing. The selection of 3PL provider affects the success of not only the firm but also the supply chain. In this study, a multi criteria decision making approach that consists of fuzzy The Decision Making Trial and Evaluation Laboratory (DEMATEL) that is used to calculate the weights of criteria and fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is utilized to evaluate the alternatives is proposed for the selection of 3PL providers. In order to show the applicability and effectiveness of the proposed approach, a case study that consists of three decision makers, seven criteria and five alternatives is obtained to select two cargo companies for a firm that produces heat systems and wants to sell its specific products via internet.

Keywords

3PL provider selection, multi criteria decision making, fuzzy DEMATEL, fuzzy TOPSIS.

References

• [1] Jharkharia S., .Shankar R, “Selection of logistics service provider: An analytic network process (ANP) approach”, Omega, 35, 274 – 289. 2007.
• [2] Li F., Li L., Jin C., R.Wang, et al., “3PL supplier selection model based on fuzzy sets”, Computers &OperationsResearch, 39, 1879–1884, 2012.
• [3] Liou J.J.H., Wang H.S., Hsu C.C., Yin S.L., “A hybrid model for selection of an outsourcing provider”, Applied Mathematical Modelling, 35, 5121–5133, 2011.
• [4] Marasco A., “Third-party logistics: A literature review”, International Journal of Production Economics, 113, 127–147, 2008.
• [5] Kulak, O. and Kahraman, C., “Fuzzy Multi-Criterion Selection Among Transportation Companies Using Axiomatic Design and Analytic Hierarchy Process”, Information Sciences, 170, 191-210, 2005.
• [6] Bottani, E. ve Rizzi, A., “A Fuzzy TOPSIS Methodology to Support Outsourcing of Logistic Services”, Supply Chain Management: An International Journal, 11 (4), 294-308, 2006.
• [7] Işıklar G., Alptekin E., Büyüközkan G., “Application of a hybrid intelligent decision support model in logistics outsourcing”, Computers & Operations Research, 34, 3701–3714, 2007.
• [8] Büyüközkan G., Feyzioğlu O., Nebol E., “Selection of the strategic alliance partner in logistics value chain”, International Journal of Production Economics, 113, 148–158, 2008.
• [9] Efendigil T., Önüt S., Kongar E., “A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness”, Computers & Industrial Engineering, 54, 269–287, 2008.
• [10] Kannan G., Pokharel S., Kumar P.S., “A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider”, Resources, Conservation and Recycling, 54, 28–36, 2009.
• [11] Liu, H.-T., Wang W.-K., “An integrated fuzzy approach for provider evaluation and selection in third-party logistics”, Expert Systems with Applications, 36, 4387–4398, 2009.
• [12] Liou J.J.H., Chuang Y.-T., “Developing a hybrid multi-criteria model for selection of outsourcing providers”, Expert Systems with Applications, 37, 3755–3761, 2010.
• [13] Chen, C.-T., Pai P.-F., Hung W.-Z., “An Integrated Methodology using Linguistic PROMETHEE and Maximum Deviation Method for Third-party Logistics Supplier Selection”, International Journal of Computational Intelligence Systems, 3, 4, 438-451, 2010.
• [14] Azadi M., Saen R.F., “A new chance-constrained data envelopment analysis for selecting third-party reverse logistics providers in the existence of dual-role factors”, Expert Systems with Applications, 38, 12231–12236, 2011.
• [15] Chen Y.M., Goan M.-J., Huang P.-N., “Selection process in logistics outsourcing – a view from third party logistics provider”, Production Planning & Control, 22, 3, 308–324, 2011.
• [16] Falsini D., Fondi F., Schiraldi M. M., “A logistics provider evaluation and selection methodology based on AHS, DEA and linear programming integration”, International Journal of Production Research, 50, 17, 4822–4829, 2012.
• [17] Wong J.-T., “DSS for 3PL provider selection in global supply chain: combining the multi-objective optimization model with experts’ opinions”, Journal of Intelligent Manufacturing, 23 (3), 599-614, 2012.
• [18] Senthil S., Srirangacharyulu B., Ramesh A., “A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics”, Expert Systems with Applications, 41 (1), 50-58, 2014.
• [19] Zhang G., Shang J., Li W., “An information granulation entropy-based model for third-party logistics providers evaluation”, International Journal of Production Research, 50, 1, 177–190, 2012.
• [20] Hsu C.-C., Liou J.J.H., Chuang Y.-C., “Integrating DANP and modified grey relation theory for the selection of an outsourcing provider”, Expert Systems with Applications, 40, 2297–2304, 2013.
• [21] Maloni, M.J., Carter, C.R., “Opportunities for research in third-party logistics”, Transportation Journal, 45 (2), 23–38, 2006.
• [22] Özbek A. ve Eren T. “Üçüncü parti lojistik firma seçiminde kullanılan çok ölçütlü karar verme yöntemleri: literatür araştırması” Sigma Mühendislik ve Fen Bilimleri Dergisi, 31, 178-202, 2013.
• [23] Zadeh L.A., “Fuzzy sets”, Information and Control, 8, 338–353, 1965.
• [24] Wu W-W. ve Lee Y-T., “Developing global managers’ competencies using the fuzzy DEMATEL method”, Expert Systems with Applications, 32, 499–507, 2007.
• [25] Aksakal E. ve Dağdeviren M., “ANP ve DEMATEL yöntemleri ile personel seçimi problemine bütünleşik bir yaklaşım”, Gazi Uni. Journal of Eng. and Arc., 25 (4), 905-910, 2010. [26] Shieh, J., Wub, H-H. and Kuan-Kai Huang, “A DEMATEL method in identifying key success factors of hospital service quality”, Knowledge-Based Systems, 23, 277–282, 2010.
• [27] Liou J.J.H., Tzeng G-H., Chang H-C., “Airline safety measurement using a hybrid model”, Journal of Air Transport Management, 13 (4), 243-249, 2007.
• [28] Wu W-W., “Choosing knowledge management strategies by using a combined ANP and DEMATEL approach”, Expert Systems with Applications, 35 (3), 828-835, 2008.
• [29] Büyüközkan G., Öztürkcan D., “An integrated analytic approach for Six Sigma project selection”, Expert Systems with Applications, 37 (8), 5835-5847, 2010.
• [30] Liou J.J.H., Chuang Y-T., “Developing a hybrid multi-criteria model for selection of outsourcing providers”, Expert Systems with Applications, 37 (5), 3755-3761, 2010.
• [31] Hsu C-W., Kuo T-C., Chen S-H., Hu A.H., “Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management”, Journal of Cleaner Production, 56, 164-172, 2013.
• [32] Lin R-J., “Using fuzzy DEMATEL to evaluate the green supply chain management practices”, Journal of Cleaner Production, 40, 32-39, 2013.
• [33] Wang T.-C., “The interactive trade decision-making research: An application case of novel hybrid MCDM model”, Economic Modelling, 29, 926–935, 2012.
• [34] Kuo M-S., “Optimal location selection for an international distribution center by using a new hybrid method”, Expert Systems with Applications, 38, 7208–7221, 2011.
• [35] Baykasoglu A., Kaplanoglu V., Durmusoglu Z.D.U., Sahin C., “Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection, Expert Systems with Applications, 40, 899–907, 2013.
• [36] Zhou Q., Huang W., Zhang Y., “Identifying critical success factors in emergency management using a fuzzy DEMATEL method”, Safety Science, 49, 243–252, 2011.
• [37] Choua Y-C., Sun C-C., Yen H-Y., “Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach”, Applied Soft Computing, 12, 64–71, 2012.
• [38] Organ A., “Bulanık Dematel Yöntemiyle Makine Seçimini Etkileyen Kriterlerin Değerlendirilmesi”, Ç.Ü. Sosyal Bil. Ens. Dergisi, 22 (1), 157-172, 2013.
• [39] Hwang C. L., Yoon K. P., “Multiple attribute decision making: Methods and applications”, New York: Springer-Verlag, 1981.
• [40] Ertuğrul İ., Karakaşoğlu N., “Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods”, Expert Systems with Applications, 36, 1, 702-715, 2009.
• [41] Wang Y-M., Elhag T.M.S., “Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment”, Expert Systems with Applications, 31, 2, 309-319, 2006.
• [42] Chu T. C., “Selecting plant location via a fuzzy TOPSIS approach”, International Journal of Advanced Manufacturing Technology, 20, 859–864, 2002.
• [43] Chu, T. C., Lin, Y. C., “A fuzzy TOPSIS method for robot selection”, International Journal of Advanced Manufacturing Technology, 21, 284–290, 2003.
• [44] Lai Y-J., Liu T-Y., Hwang C-L., “TOPSIS for MODM”, European Journal of Operational Research, 76, 3, 11, 486-500, 1994.
• [45] Wang, J., Liu, S. Y., Zhang, J., “An Extension of TOPSIS for Fuzzy MCDM based on vague set theory”, Journal of Systems Science and Systems Engineering, 14, 1, 73–84, 2005.
• [46] Chen C-T., “Extensions of the TOPSIS for group decision-making under fuzzy environment”, Fuzzy Sets and Systems, 114, 1-9, 2000.
• [47] Kulak O., Durmuşoğlu M.B., Kahraman C., “Fuzzy multi-attribute equipment selection based on information axiom”, Journal of Materials Processing Technology, 169, 3, 337-345, 2005.
• [48] Kahraman C., Çevik S., Ates N.Y., Gülbay M., “Fuzzy multi-criteria evaluation of industrial robotic systems”, Computers & Industrial Engineering, 52, 4, 414-433, 2007.
• [49] Önüt S., Soner S., “Transshipment site selection using the AHS and TOPSIS approaches under fuzzy environment”, Waste Management, 28, 9, 1552-1559, 2008.
• [50] Yang T., Hung C-C., “Multiple-attribute decision making methods for plant layout design problem”, Robotics and Computer-Integrated Manufacturing, 23, 1, 126-137, 2007.