A Comparative Analysis Approach Based on Fuzzy AHP, TOPSIS and PROMETHEE for the Selection Problem of GSCM Solutions
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33103
A Comparative Analysis Approach Based on Fuzzy AHP, TOPSIS and PROMETHEE for the Selection Problem of GSCM Solutions

Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

Abstract:

Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, FAHP, TOPSIS, PROMETHEE, decision support system.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1474833

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 939

References:


[1] Poulton, M. M., Jagers, S. C., Linde, S., VanZyl, D., Danielson, L. J., Matti, S., 2013. State of the world’s nonfuel mineral resources: supply, demand, and socioinstitu- tional fundamentals. Annu. Rev. Environ. Resour. 38(1), 345–371.
[2] Jayant A, Azhar M (2014) Analysis of the Barriers for Implementing Green Supply Chain Management (GSCM) Practices: An Interpretive Structural Modeling (ISM) Approach. Procedia Engineering 97: 2157–2166.
[3] Govindan K, Khodaverdi R, Vafadarnikjoo A (2015) Intuitionistic fuzzy based DEMATEL method for developing green practices and performances in a green supply chain. Expert Systems with Applications. doi:10.1016/j.eswa.2015.04.030.
[4] Lee. V-H., Ooi. K-B.. Y-L Chong. A.. Seow. C.. (2014). Creating technological innovation via green supply chain management: An empirical analysis. Expert Systems with Applications. 41 (16) 6983–6994.
[5] Govindan K, Kaliyan M, Kannan D, Haq AN (2014) Barriers analysis for green supply chain management implementation in Indian industries using analytic hierarchy process. International Journal of Production Economics 147: 555–568.
[6] Amindoust, A., Ahmed, S., Saghafinia, A., & Bahreininejad, A. (2012). Sustainable supplier selection: A ranking model based on fuzzy inference system. Applied Soft Computing, 12(6), 1668–1677.
[7] Grimm, J. H., Hofstetter, J. S., & Sarkis, J. (2016). Exploring sub-suppliers' compliance with corporate sustainability standards. Journal of Cleaner Production, 112, 1971-1984.
[8] Xie G (2015) Modeling decision processes of a green supply chain with regulation on energy saving level. Computers & Operations Research 54: 266–273.
[9] Diabata A, Govindan K, (2011) An analysis of the drivers affecting the implementation of green supply chain management. Resources, Conservation and Recycling 55 (6): 659-667.
[10] Green Jr, KW, Zelbst PJ, Meacham J, Bhadauria VS (2012) Green Supply Chain Management Practices: Impact on Performance. Supply Chain Management: An International Journal 17 (3): 290–305.
[11] Mathiyazhagan K, Govindan K, NoorulHaq A, Geng Y (2013) An ISM approach for the barrier analysis in implementing green supply chain management. Journal of Cleaner Production 47: 283-297.
[12] Muralidhar P, Ravindranath K, Srihari V (2012) Evaluation of Green Supply Chain Management Strategies Using Fuzzy AHP and TOPSIS, IOSR Journal of Engineering 2(4): 824-830.
[13] Patil S-K, Kant R (2014) A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers. Expert Systems with Applications 41(2): 679–693.
[14] Chen C-C, Shih H-S, Shyur H-J, Wuc K-S (2012) A business strategy selection of green supply chain management via an analytic network process. Computers and Mathematics with Applications 64 (8): 2544-2557.
[15] Luthra S, Qadri MA, Garg D, Haleem A (2014) Identification of critical success factors to achieve high green supply chain management performances in Indian automobile industry. International Journal of Logistics Systems and Management 18(2): 170-199.
[16] Rozar NM, Mahmood WHW, Ibrahim A, Razik MA (2015) A Study of Success Factors in Green Supply Chain Management in Manufacturing Industries in Malaysia. Journal of Economics, Business and Management 3(2): 287-291.
[17] Saaty TL (1980) The Analytic Hierarchy Process, McGraw-Hill.
[18] Yang CC, Chen BS (2004) Key quality performance evaluation using fuzzy AHP, Journal of the Chinese Institute of Industrial Engineers 21(6): 543–550.
[19] Gil-Lafuente, A. M., Merigó, J. M., & Vizuete, E. (2014). Analysis of luxury resort hotels by using the Fuzzy Analytic Hierarchy Process and the Fuzzy Delphi Method. Economic Research-Ekonomska Istraživanja, 27(1), 244–266. doi:10.1080/1331677x.2014.952106.
[20] Boutkhoum, O., Hanine, M., Tikniouine, A., & Agouti, T. (2015). Multi-criteria decisional approach of the OLAP analysis by fuzzy logic: green logistics as a case study. Arabian Journal for Science and Engineering, 40(8), 2345-2359.
[21] Hanine, M., Boutkhoum, O., Agouti, T., & Tikniouine, A. (2017). A new integrated methodology using modified Delphi-fuzzy AHP-PROMETHEE for Geospatial Business Intelligence selection. Information Systems and e-Business Management, 15(4), 897-925.
[22] Boutkhoum, O., Hanine, M., Boukhriss, H., Agouti, T., & Tikniouine, A. (2016). Multi-criteria decision support framework for sustainable implementation of effective green supply chain management practices. SpringerPlus, 5(1), 664.
[23] Gumus AT (2009) Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology, Expert Systems with Applications 36(2): 4067-4074.
[24] Brans JP, Vincke P (1985) A preference ranking organization method. Management Science 31 (6): 647–656.
[25] Behzadian M, Kazemzadeh RB, Albadvi A, Aghdasi M (2010) PROMETHEE: a comprehensive literature review on methodologies and applications. European Journal of Operational Research 200 (1): 198–215.
[26] Mousavi SM, Tavakkoli-Moghaddam R, Heydar M, Ebrahimnejad S (2013) Multi-Criteria Decision Making for Plant Location Selection: An Integrated Delphi-AHP-PROMETHEE Methodology. Arab J Sci Eng 38(5): 1255–1268.
[27] Kilic HS, Zaim S, Delen D (2015) Selecting “The Best” ERP system for SMEs using a combination of ANP and PROMETHEE methods. Expert Systems with Applications 42(5): 2343–2352.
[28] Kazem S, Hadinejad F (2015) PROMETHEE technique to select the best radial basis functions for solving the 2-dimensional heat equations based on Hermite interpolation. Engineering Analysis with Boundary Elements 50:29–38.
[29] Boutkhoum, O., Hanine, M., Agouti, T., & Tikniouine, A. (2016). Selection problem of cloud solution for big data accessing: fuzzy AHP-PROMETHEE as a proposed methodology. Journal of Digital Information Management, 14(6).
[30] Hanine, M., Boutkhoum, O., El Maknissi, A., Tikniouine, A., & Agouti, T. (2016). Decision making under uncertainty using PEES–fuzzy AHP–fuzzy TOPSIS methodology for landfill location selection. Environment Systems and Decisions, 36(4), 351-367.
[31] Tuzkaya, U. R. (2009). Evaluating the environmental effects of transportation modes using an integrated methodology and an application. International Journal of Environmental Science & Technology, 6(2), 277–290. doi:10.1007/bf03327632.
[32] Hwang C-L, Yoon K (1981) Multiple attribute decision making: methods and applications a state-of-the-art survey. Lecture notes in economics and mathematical systems, vol 186, 1st edn. Springer, Berlin, Heidelberg, pp 58–191. doi:10.1007/978-3-642-48318-9_3.
[33] Perron GM (2005) Barriers to Environmental Performance Improvements in Canadian SMEs. Dalhousie University, Canada.
[34] Revell A, Rutherfoord R (2003) UK environmental policy and the small firm: broadening the focus. Business Strategy and the Environment 12(1): 26-35.
[35] Ahmad N, Daghfous A (2010) Knowledge sharing through inter-organizational knowledge networks Challenges and opportunities in the United Arab Emirates. European Business Review 22 (2): 153–174.
[36] De Giovanni PD, Vinzi VE (2012) Covariance versus Component-based Estimations of Performance in Green Supply Chain Management. International Journal of Production Economics 135 (2): 907–916.
[37] Lee VH, Ooi KB, Chong AYL, Lin B (2013) A Structural Analysis of Greening the Supplier, Environmental Performance and Competitive Advantage. Production Planning & Control. DOI:10.1080/09537287.2013.859324.
[38] Zailani S, Jeyaraman K, Vengadasan G, Premkumar R (2012) Sustainable Supply Chain Management (SSCM) in Malaysia: A Survey. International Journal of Production Economics 140(1):330–340.
[39] Sheu J-B, Chou Y-H, Hu C-C (2005) An integrated logistics operational model for green-supply chain management. Transportation Research Part E: Logistics and Transportation Review 41(4):287–313.
[40] Al-Mutawah K, Lee V, Cheung Y (2009) A new multi-agent system framework for tacit knowledge management in manufacturing supply chains. Journal of Intelligent Manufacturing 20 (5): 593–610.
[41] Wong WP, Wong PS (2011) Supply chain management, knowledge management capability, and their linkages towards firm performance. Business Process Management Journal 17(6): 940–964.
[42] Wang F, Lai X, Shi N (2011) A multi-objective optimization for green supply chain network design, Decision Support Systems 51(2): 262–269.
[43] Choy K, Chow H, Tan K., Chan C, Mok S, Wang Q (2008) Leveraging the supply chain flexibility of third party logistics – hybrid knowledge-based system approach. Expert Systems with Applications 35(4): 1998–2016.
[44] Johnson ME, Whang S (2002) E-business and supply chain management: An overview and framework. Production and Operations Management 11(4):413–423.
[45] Modi SB, Mabert VA (2007) Supplier development: Improving supplier performance through knowledge transfer. Journal of Operations Management 25 (1): 42–64.
[46] Promethee (2018). Multicriteria Decision Aid Methods, Modeling and Software. http://www.promethee-gaia.net/visual-promethee.html.