Logistics Distribution Centers Location Problem under Fuzzy Environment

  • Muhammad Hashim
  • Liming Yao
  • Abid Hussain Nadeem
  • Muhammad Nazim
  • Muhammad Nazam
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 242)

Abstract

Logistics distribution centers location problem is concerned with how to select distribution centers from the potential set for minimizing cost and fulfill the demand. This paper aims at multi-objective optimization for three-echelon supply chain architecture consisting of manufacturer, distribution centers (DCs) and customers. The key design decisions considered are: the number and location of distribution centers, the quantity of products to be shipped from manufacturer to DCs and then from DCs to customers. The present study mainly investigates the proposed problem under fuzzy environment and the uncertain model is converted into a deterministic form by the expected value measure. The approximate best solution of the model is provided using fuzzy simulation. A numerical example is used to illustrate the effectiveness of the proposed model and solution approach.

Keywords

Distribution center location problem Multi-objective model Expected value measure Fuzzy programming method 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Perl J, Daskin MS (1985) A warehouse location-routing problem. Transportation Research Part B: Methodological 19(5):381–96Google Scholar
  2. 2.
    Aksen D, Altinkemer K (2008) A location-routing problem for the conversion to the click- and-mortar retailing. European Journal of Operational Research 186(2):554–575Google Scholar
  3. 3.
    Amiri A (2006) Designing a distribution network in a supply chain system: Formulation and efficient solution procedure. European Journal of Operational Research 171(2):567–576Google Scholar
  4. 4.
    Syam S (2002) A model and methodologies for the location problem with logistical components. Computer Operations Research 29(9):1173–1193Google Scholar
  5. 5.
    Chen C (2001) A fuzzy approach to select the location of the distribution center. Fuzzy Sets and Systems 118(1):65–73Google Scholar
  6. 6.
    Yang L, Ji X, Gao Z et al (2007) Logistics distribution centers location problem and algorithm under fuzzy environment. Computational and Applied Mathematics 208(2):303–315Google Scholar
  7. 7.
    Moreno J, Moreno-Vega J, Verdegay J (2004) Fuzzy location problems on networks. Fuzzy Sets and Systems 142(3):393–405Google Scholar
  8. 8.
    Lu Z, Bostel N (2007) A facility location model for logistics systems including reverse flows: The case of remanufacturing activities. Computers and Operations Research 34(2):299–323Google Scholar
  9. 9.
    Sheu JB (2003) Locating manufacturing and distribution centers: An integrated supply-chain based spatial interaction approach. Transportation Research Part E: Logistics and Transportation Review 39(5):381–397Google Scholar
  10. 10.
    Klose A, Drexl A (2005) Facility location models for distribution system design. European Journal of Operational Research 162(1):4–9Google Scholar
  11. 11.
    Xu J, Yao L, Zhao X (2011) A multi-objective chance-constrained network optimal model with random fuzzy coeffcients and its application to logistics distribution center location problem. Fuzzy Optimization Decision Making 10(3):255–285Google Scholar
  12. 12.
    Liu Q, Xu J (2011) A study on facility location–allocation problem in mixed environment of randomness and fuzziness. Journal of Intelligent Manufacturing 22(3):389–398Google Scholar
  13. 13.
    Sun H, Gao Z, Wu J (2008) A bi-level parogramming model and solution algorithm for the location of logistics distribution centers. Applied Mathematical Modelling 32(4):610–616Google Scholar
  14. 14.
    Shankar BL, Basavarajappa S, Chen JCH et al (2013) Location and allocation decisions for multi-echelon supply chain network: A multi-objective evolutionary approach. Expert Systems with Applications 40(2):551–562Google Scholar
  15. 15.
    Xu J, Wei P(2012) A bi-level model for location-allocation problem of construction and demolition waste management under fuzzy random environment. International Journal of Civil Engineering 10(1):1–1Google Scholar
  16. 16.
    Cohen MA, Lee HL (1989) Resource deployment analysis of global manufacturing and distribution networks. Journal of Manufacturing and Operations Management 2(2):81–104Google Scholar
  17. 17.
    Tsiakis P, Shah N, Pantelides CC (2001) Design of multi-echelon supply chain networks under demand uncertainty. Industrial and Engineering Chemistry Research 40(16):3585–3604Google Scholar
  18. 18.
    Zadeh LA (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 1(1):38–41Google Scholar
  19. 19.
    Su R, Yang D, Pearn WL (2011) Decision-making in a single-period inventory environment with fuzzy demand. Expert Systems with Applications 38(3):1909–1916Google Scholar
  20. 20.
    Xu J, Zhou X (2011) Fuzzy like multi objective decision making. Springer-Verlag, Berlin, HdidelbergGoogle Scholar
  21. 21.
    Keshteli MH (2011) The allocation of customers to potential distribution centers in supply chain networks: GA and AIA approaches. Applied Soft Computing 11(2):2069–2078Google Scholar
  22. 22.
    Owen SH, Daskin MS (1998) Strategic facility location: A review. European Journal of Operational Research 111(3):423–447Google Scholar
  23. 23.
    Rommelfanger H (1996) Fuzzy linear programming and applications. European Journal Operational Research 92(3):512–527Google Scholar
  24. 24.
    Slowinski R, Teghem J (1990) Stochastic versus fuzzy approaches to multiobjective mathematical programming under uncertainty. Kluwer Academic Publishers, DordrechtGoogle Scholar
  25. 25.
    Rommelfanger H (2004) The advantages of fuzzy optimization models in practical use. Fuzzy Optimization Decision Making 3(4):295–309Google Scholar
  26. 26.
    Dubois D, Prade H (1994) Possibility theory: An approach to computerized processing of uncertainty. Plenum Press, New YorkGoogle Scholar
  27. 27.
    Zimmermann H (1978) Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems 1(1):45–55Google Scholar
  28. 28.
    Sakawa M (1993) Fuzzy sets and interactive multiobjective optimization. Plenum Press New YorkGoogle Scholar
  29. 29.
    Rommelfanger H (1996) Fuzzy linear programming and applications. European Journal of Operational Research 92(3):512–527Google Scholar
  30. 30.
    Selim H, Araz C, Ozkarahan I (2008) Collaborative production-distribution planning in supply chain: A fuuzy goal programming approach. Transportation Research part E 44(3):396–419Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Muhammad Hashim
    • 1
  • Liming Yao
    • 1
  • Abid Hussain Nadeem
    • 1
  • Muhammad Nazim
    • 1
  • Muhammad Nazam
    • 1
  1. 1.Business SchoolSichuan UniversityChengduPeople’s Republic of China

Personalised recommendations