An Integrated Approach of Fuzzy AHP and Fuzzy TOPSIS to Select Logistics Service Provider

Ponnuboina Kishore; G. Padmanabhan

doi:10.1515/jmsp-2015-0017

Article

An Integrated Approach of Fuzzy AHP and Fuzzy TOPSIS to Select Logistics Service Provider

Ponnuboina Kishore and G. Padmanabhan

Published/Copyright: March 15, 2016

Published by

Become an author with De Gruyter Brill

Author Information

From the journal Journal for Manufacturing Science and Production Volume 16 Issue 1

Abstract

In India, Manufacturing companies are primarily being concentrated on the production activities which led to drastic improvement of outsourcing logistics process to third party logistics (3PLS), consequently a strong outsourcing logistics can be observed over the next two decades for the development of a company. It may therefore be noted that the enhancement and extrusion are necessary in order to effectively asses risk and opportunities. To achieve this, the best logistics service provider which leads to the growth of organisation and industry has to be selected. The present work aims at the integration of Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in Fuzzy environment. The integration is carried out with more consistency while evaluating and selecting the best Logistics service provider based on ten coordination criteria viz. Custom Clearance, On Time Delivery, Number of Customers Handled, Placement Percentage, Tracking Status, Service Quality, Solving of Issues, Collecting Proof of Delivery, Region and Price. Fuzzy AHP is used to calculate relative weights of each coordination criterion. Logistics service providers are ranked based on closeness coefficient, calculated for each LSP using Fuzzy TOPSIS. By this method the LSP5 has selected as best logistic service provider among the seven LSP for battery manufacturing company.

Keywords: multi criteria decision making (MCDM); fuzzy Analytic hierarchy process (FAHP); fuzzy technique for order preference by similarity to ideal solution (FTOPSIS); logistics service provider (LSP); pairwise comparison matrix; closeness coefficient (CC)

PACS: 89.20.Bb

References

1. Ajakaiye OI. The role of logistics service providers in the logistics firms supply chain. International Logistics and Supply Chain Management, Master thesis, June 2012.Search in Google Scholar

2. Li T, Jin J, Li C. Refractured well selection for multi criteria group decision making by integrating fuzzy AHP with Fuzzy TOPSIS based on interval-typed fuzzy numbers. J Appl Math 2012;2012:21.Search in Google Scholar

3. Stock GN, Greis NP, Kasarda JD. Logistics, strategy and structure: a conceptual framework. Int J Oper Prod Manage 1998;18:37–52.Search in Google Scholar

4. Zadeh LA. The concept of a linguistic variable and its application to approximate reasoning-II. Inf Sci 1975;8:301–57.Search in Google Scholar

5. Aktepe A, Ersoz S. A fuzzy analytic hierarchy process model for supplier selection and a case study. Int J Res Dev 2011;3:33–7.Search in Google Scholar

6. Mahmood Zadeh S, Shahrabi J, Pariazar, M, Zaeri MS. Project selection by using fuzzy AHP and TOPSIS technique. Int J Hum Social Sci 2007;1:135–40.Search in Google Scholar

7. Zadeh LA. Fuzzy sets. Int J Inf Control 1965;8:338–53.Search in Google Scholar

8. Bilsel RU, Buyukozkan G, Ruan D. A fuzzy preference-ranking model for a quality evaluation of hospital websites. Int J Intell Syst 2006;21:1181–97.Search in Google Scholar

9. Chan FTS, Kumar N. Global supplier development considering risk factors using fuzzy Extended AHP-based approach. Int J Manage Sci 2007;35:417–31.Search in Google Scholar

10. Chung SH, Lee AH, Pearn WL. Product mix optimization for semiconductor manufacturing based on AHP and ANP analysis. Int J Adv Manuf Technol 2005;25:1144–56.Search in Google Scholar

11. Sodhi B, Prabhakar TV A simplified description of Fuzzy TOPSIS. arxiv:1205.5098v1 [cs.AI]23 May 2012.Search in Google Scholar

12. Akman G, Alkan A. Measurement of supplier performance at supply chain management by using Fuzzy AHP method: a study at automotive subcontractor industry. Istanbul Commerce Univ J Sci 2006;5:3–46.Search in Google Scholar

13. Chang DY. Extent analysis and synthetic decision. Optim Tech Appl 1992;1:352.Search in Google Scholar

14. Pedrycz PG. Human decision – making models for social sciences. Heidelberg: Springer, 2014.Search in Google Scholar

15. Baltacıoğlu T, Kaplan MD. The era collaboration through supply chain network. 4th International Logistics and Supply Chain Congress, 2006.Search in Google Scholar

Received: 2015-9-25

Accepted: 2016-2-5

Published Online: 2016-3-15

Published in Print: 2016-3-1

You are currently not able to access this content.

Articles in the same Issue

https://doi.org/10.1515/jmsp-2015-0017

Keywords for this article

multi criteria decision making (MCDM); fuzzy Analytic hierarchy process (FAHP); fuzzy technique for order preference by similarity to ideal solution (FTOPSIS); logistics service provider (LSP); pairwise comparison matrix; closeness coefficient (CC)