Logistic Management Employing Tabu Search and Neural Network Algorithms: A Case Study

  • Isidro Peña García-Pardo
  • Fausto Pedro García Márquez
Conference paper
Part of the Lecture Notes in Management and Industrial Engineering book series (LNMIE)

Abstract

This paper presents a real case study of a routing problem in a Spanish firm leader in the fresh food industry. The main objective is to improve profits and competitiveness based on logistic operations, minimizing the transportation cost employing the tabu search and neural network meta-heuristics algorithms. The simplest case considered is the Traveling Salesman Problem (TSP). The real case study presented in this paper there are capacity restrictions and different demands at each node, therefore the problem is solved as a Capacitated Vehicle Routing Problem (CVRP).

Keywords

CVRP Neural network Tabu Search Logistic Management 

References

  1. 1.
    Baldacci R, Toth P, Vigo D (2007) Recent advances in vehicle routing exact algorithms, 4OR. Q J Oper Res 5:269–298CrossRefMATHMathSciNetGoogle Scholar
  2. 2.
    Bektas T (2006) The multiple traveling salesman problem: an overview of formulations and solution procedures. Omega 34:209–219.Google Scholar
  3. 3.
    Brandão J (2011) A tabu search algorithm for the heterogeneous fixed fleet vehicle routing problem. Comput Oper Res 38:140–151CrossRefMATHMathSciNetGoogle Scholar
  4. 4.
    Cordeau JF, Laporte G (2004) Tabu search heuristics for the vehicle routing problem. In: Rego C, Alidaee B (eds) Metaheuristic optimization via memory and evolution: Tabu search and scatter search. Kluwer, Boston, pp 145–163Google Scholar
  5. 5.
    Euchi J, Chabchoub H (2010) A hybrid Tabu Search to solve the heterogeneous fixed fleet vehicle routing problem. Logist Res 2:3–11CrossRefGoogle Scholar
  6. 6.
    Faulin J (2003) Applying MIXALG procedure in a routing problem to optimize food product delivery. Omega 31:387–395CrossRefGoogle Scholar
  7. 7.
    Faulin J, Juan A, Lera F, Grasman C (2011) Solving the capacitated vehicle routing problem with environmental criteria based on real estimations in road transportation: a case study. Proced-Soc Behav Sci 20:323–334CrossRefGoogle Scholar
  8. 8.
    Ganesh K, Nallathambi AS, Narendran TT (2007) Variants, solution approaches and applications for vehicle routing problems in supply chain: agile framework and comprehensive review. Int J Agil Syst Manage 2:50–75Google Scholar
  9. 9.
    Gendreau M, Hertz A, Laporte G (1994) A tabu search heuristic for the vehicle routing problem. Manage Sci 40:1276–1290CrossRefMATHGoogle Scholar
  10. 10.
    Hsu CL, Feng S (2003) Vehicle routing problem for distributing refrigerated food. J East Asia Soc Transp Stud 5:2261–2272Google Scholar
  11. 11.
    Leung KS, Jin HD, Xu ZB (2004) An expanding self-organizing neural network for the traveling salesman problem. Neurocomputing 62:267–292CrossRefGoogle Scholar
  12. 12.
    Ma H, Cheang B, Lim A, Zhan L, Zhu Y (2012) An investigation into the vehicle routing problem with time windows and link capacity constraints. Omega 40:336–347CrossRefGoogle Scholar
  13. 13.
    Miller CE, Tucker AW, Zemlin RA (1960) Integer programming formulation of traveling salesman problems. J Assoc Comput Mach 7:326–329CrossRefMATHMathSciNetGoogle Scholar
  14. 14.
    Prindezis N, Kiranoudis CT, Kouris DM (2003) A business-to-business fleet management service provider for central food market enterprises. J Food Eng 60:203–210CrossRefGoogle Scholar
  15. 15.
    Sivanandam SN, Dumathi S, Deepa SN (2006) Introduction to neural networks using MATLAB 6.0. McGraw Hill, Delhi, pp 487–512Google Scholar
  16. 16.
    Tarantilis CD, Kiranoudis CT (2001) A meta-heuristic algorithm for the efficient distribution of perishable foods. J Food Eng 50:1–9CrossRefGoogle Scholar
  17. 17.
    Tarantilis CD, Kiranoudis CT (2002) Distribution of fresh meat. J Food Eng 51:85–91CrossRefGoogle Scholar
  18. 18.
    Toth P, Vigo D (2002) Models, relaxations and exact approaches for the capacitated vehicle routing problem. Discret Appl Math 123:487–512CrossRefMATHMathSciNetGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Isidro Peña García-Pardo
    • 1
  • Fausto Pedro García Márquez
    • 2
  1. 1.Dpto. de Administración de Empresas, Facultad de Derecho y Ciencias SocialesUniversidad de Castilla-La ManchaCiudad RealSpain
  2. 2.INGENIUM GROUP, ETSI IndustrialesUniversidad de Castilla-La ManchaCiudad RealSpain

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