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Design and Optimization of a Multi-echelon Supply Chain Network for Product Distribution with Cross-Route Costs and Traffic Factor Values

  • Asnaf Aziz
  • Razaullah
  • Iftikhar Hussain
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 513)

Abstract

Network design and optimization problems for product flow appear widely in shipping and production applications. We present a new variation to such class of problems in which the shipping cost linked with a route depends not only on the product flow moving across that route but on the product flow on other routes in the supply chain network as well. Selecting a route with fewer hurdles increases the product flow effectiveness. We consider the entire supply chain network i.e., from raw material supply to production, finished products to warehouses and then to the demand points. We formulate an integer mathematical model and present computational results for a set of test problems arising from shipping and production applications to analyze how the model performs with the varying network characteristics.

Keywords

Network design Product distribution Cross-route costs Traffic factor 

Notes

Acknowledgements

I wish to thank Prof. Dr. Imtiaz Hakeem, Department of Mechanical Engineering, SUIT, Peshawar, for his support, helpful suggestions and critical comments.

References

  1. 1.
    Longinidis P, Georgiadis MC (2014) Integration of sale and leaseback in the optimal design of supply chain networks. Omega 47:73–89CrossRefGoogle Scholar
  2. 2.
    Wang H, Mastragostino R, Swartz CLE (2016) Flexibility analysis of process supply chain networks. Comput Chem Eng 84:409–421CrossRefGoogle Scholar
  3. 3.
    Nagurney A, Liu Z, Cojocaru MG, Daniele P (2007) Dynamic electric power supply chains and transportation networks: an evolutionary variational inequality formulation. Transp Res Part E 43:624–646CrossRefGoogle Scholar
  4. 4.
    Gill A (2011) A supply chain design approach to petroleum distribution. Int J Bus Res Manage 2(1):33–44Google Scholar
  5. 5.
    Cohn A, Davey M, Schkade L, Siegel A, Wong C (2008) Network design and flow problems with cross-arc costs. Eur J Oper Res 189:890–901CrossRefGoogle Scholar
  6. 6.
    Eliiyi U, Nasibov E, Özkılçık M, Kuvvetli U (2012) Minimization of fuel consumption in city bus transportation: a case study for Izmir. Procedia-Soc Behav Sci 54:231–239CrossRefGoogle Scholar
  7. 7.
    Zhu X, Garcia-Diaz A, Jin M, Zhang Y (2014) Vehicle fuel consumption minimization in routing over-dimensioned and overweight trucks in capacitated transportation networks. J Clean Prod 85:331–336CrossRefGoogle Scholar
  8. 8.
    Leblanc LJ, Boyce DE (1986) A bi-level programming algorithm for exact solution of the network design problem with user-optimal flows. Transp Res 3:259–265CrossRefGoogle Scholar
  9. 9.
    Machado CMS, Mayerle SF, Trevisan V (2010) A linear model for compound multicommodity network flow problems. Comput Oper Res 37:1075–1086MathSciNetCrossRefGoogle Scholar
  10. 10.
    Bozorgirad S, Desa MI, Wibowo A (2012) Genetic algorithm enhancement to solve multi-source multi-product flexible multi-stage logistics network. IJCSI Int J Comput Sci 9(3):2, 157–164Google Scholar
  11. 11.
    Kalaitzidou MA, Longinidis P, Georgiadis MC (2015) Optimal design of closed-loop supply chain networks with multifunctional nodes. Comput Chem Eng 80:73–91CrossRefGoogle Scholar
  12. 12.
    Barnhart C, Hane CA, Vance PH (2000) Using branch-and-price-and-cut to solve origin-destination integer multicommodity flow problems. Oper Res 48(2):318–326CrossRefGoogle Scholar
  13. 13.
    Nielsen CA, Armacost AP, Barnhart C, Kolitz SE (2004) Network design formulations for scheduling U.S. Air Force channel route missions. Math Comput Model 39:925–943MathSciNetCrossRefGoogle Scholar
  14. 14.
    Pant RR, Prakash G, Farooquie JA (2015) A framework for traceability and transparency in the dairy supply chain networks. Procedia-Soc Behav Sci 189:385–394CrossRefGoogle Scholar
  15. 15.
    Yolmeh A, Salehi N (2015) An outer approximation method for an integration of supply chain network designing and assembly line balancing under uncertainty. Comput Ind Eng 83:297–306CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Mechanical Engineering TechnologyUniversity of TechnologyNowsheraPakistan
  2. 2.Department of Industrial EngineeringUniversity of Engineering and TechnologyPeshawarPakistan

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