Modelling the logistic processes using fuzzy decision approach

Yıl 2019, Cilt: 48 Sayı: 2, 552 - 563, 01.04.2019

Saima Mustafa , İshrat Fatimah Young Bae Jun

Öz

Logistic processes deal with the information about producing and distributing goods and services from one place to another to fulfill the customer requirements. Every kind of business requires the proper functioning of logistic processes for the success of company or organization. In retail businesses, facility location for logistic processes serves as a backbone and the success or a failure of the company depends upon the geographical location of the company. It is a multiple criteria decision making problem involves multiple criteria to analyze the proper location of a company. In this research work, at first, we developed a multi criteria based structural model in retail facility location selection based on logistic processes. Then by using fuzzy modelling technique, the criteria are converted into triangular fuzzy numbers. We have adopted the technique of order preference similarity to ideal solutions for finding the best alternative. We have also applied the sensitivity analysis on the suggested modelling technique and found the same alternative as best with high degree of certainty which confirms the reliability of the proposed modelling technique.

Anahtar Kelimeler

Retail logistic processes, Facility location, Decision making, Triangular fuzzy numbers, Best alternative

Kaynakça

• Abdi, M. R. Fuzzy multi-criteria decision model for evaluating reconfigurable machines, International Journal of Production Economics 117 (1), 1, 2009.
• Akman, G. and Baynal, K. Logistics service provider selection through an integrated fuzzy multicriteria decision making approach, Journal of Industrial Engineering 1, 2014.
• Cakir, E., Tozan, H. and Vayvay, O. A method for selecting third party logistic service provider using fuzzy AHP, Journal of Naval Science and Engineering 5 (3), 38, 2009.
• Chen, S., Liu, J., Wang, H. and Augusto, J. C. Ordering based decision makinga survey, Information Fusion 14 (4), 521-531, 2013.
• Christopher, M. Logistics & supply chain management, Pearson UK, 2016.
• Dornier, P. P., Ernst, R., Fender, M. and Kouvelis, P. Global operations and logistics: Text and cases, John Wiley & Sons, 2008.
• Girvica, O. Optimization of the Supply Chain Process for the Logistic Centre, Transport and Telecommunication TSI journal 11 (2), 12, 2010.
• Gursel, G. Healthcare, uncertainty, and fuzzy logic, Digital Medicine 2 (3), 101, 2016.
• Jae, M. and Moon, J. H. Use of a fuzzy decision-making method in evaluating severe accident management strategies, Annals of Nuclear Energy 29 (13), 1597-1606, 2002.
• Kiker, G. A., Bridges, T. S., Varghese, A., Seager, T. P. and Linkov, I. Application of multicriteria decision analysis in environmental decision making, Integrated environmental assessment and management 1 (2), 95-108, 2005.
• Lopez Gonzalez, E., Rodriguez-Fernandez, M. A. and Mendana Cuervo, C. The logistic decision making in management accounting with genetic algoritms and fuzzy sets, Mathware & soft computing 7 (1), 2-3, 2000.
• Mentzer, J. T., Stank, T. P. and Esper, T. L. Supply chain management and its relationship to logistics, marketing, production, and operations management, Journal of Business Logistics 29 (1), 31-46, 2008.
• Ahlstrand, B., Lampel, J. and Mintzberg, H. SStrategy Safari: A guided tour through the wilds of strategic management, Simon and Schuster, 2001.
• Momeni, M., Fathi, M. R., Zarchi, M. K. and Azizollahi, S. A Fuzzy TOPSIS-based approach to maintenance strategy selection: A case study, Middle-East Journal of Scientific Research 8 (3), 699-706, 2011.
• Monghasemi, S., Nikoo, M. R., Fasaee, M. A. K. and Adamowski, J. A novel multi criteria decision making model for optimizing timecostquality trade-off problems in construction projects, Expert systems with applications 42 (6), 3089-3104, 2015.
• Mudambi, R. Location, control and innovation in knowledge-intensive industries, Journal of economic Geography 8 (5), 699-725, 2008.
• Oliva, R. and Kallenberg, R. Managing the transition from products to services, International journal of service industry management 14 (2), 160-172, 2003.
• Rushton, A., Croucher, P. and Baker, P. The handbook of logistics and distribution management: Understanding the supply chain, Kogan Page Publishers, 2014.
• Silva, C. A., Sousa, J. M. C. and Runkler, T. A. Runkler. Optimization of logistic systems using fuzzy weighted aggregation, Fuzzy Sets and Systems 158 (17), 1947-1960, 2007.
• Sun, C., Xiang, Y., Jiang, S. and Che, Q. A supply chain risk evaluation method based on fuzzy TOPSIS, International Journal of Safety and Security Engineering 5 (2), 150-161, 2015.
• Sharma, S. and Balan, S. An integrative supplier selection model using Taguchi loss function, TOPSIS and multi criteria goal programming, Journal of Intelligent Manufacturing 24 (6), 1123-1130, 2013.
• Tseng, Y., Yue, W. L. and Taylor, M. A. P. The role of transportation in logistics chain, Eastern Asia Society for Transportation Studies 5 (1),1660, 2005.
• Velasquez, M. and Hester, P. T. An analysis of multi-criteria decision making methods, International Journal of Operations Research 10 (2), 56-66, 2013.
• Várlaki, P. and Vadvári, T. Queuing Models and Subspace Identification in Logistics, Acta Technica Jaurinensis 8 (1), 63-76, 2015.
• Wang, H. B. and Wang, Z.W. Study on the method and procedure of logistics system modeling and simulation, In Proceedings of the 2nd International Conference on Science and Social Research, 776-780, 2013.