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A two-phase ant colony algorithm for multi-echelon defective supply chain network design


  • Wang, H.S.


Supply chain system is an integrated production system of a product. In the past researches, this system was often assumed to be an equilibrium structure, but in real production process, some members in this system usually cannot effectively complete their production task because of the losses of production, which will reduce the performance of the whole supply chain production system. This supply chain with the losses of production is called the defective supply chain (DSC) system. This research will discuss the partner selection and the production-distribution planning in this DSC network system. Besides the cost of production and transportation, the reliability of the structure and the unbalance of this system caused by the losses of production are considered. Then a germane mathematical programming model is developed for solving this problem. Due to the complex problem and in order to get a satisfactory near-optimal solution with great speed, this research proposes seeking the solution with the solving model based on ant colony algorithm. The application results in real cases show that the solving model presented by this research can quickly and effectively plan the most suitable type of the DSC network and decision-making of the production-distribution. Finally, a comparative numerical experiment is performed by using the proposed approach and the common single-phase ant colony algorithm (SAC) to demonstrate the performance of the proposed approach. The analysis results show that the proposed approach can outperform the SAC in partner selection and production-distribution planning for DSC network design.

Suggested Citation

  • Wang, H.S., 2009. "A two-phase ant colony algorithm for multi-echelon defective supply chain network design," European Journal of Operational Research, Elsevier, vol. 192(1), pages 243-252, January.
  • Handle: RePEc:eee:ejores:v:192:y:2009:i:1:p:243-252

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    References listed on IDEAS

    1. Weber, Charles A. & Desai, Anand, 1996. "Determination of paths to vendor market efficiency using parallel coordinates representation: A negotiation tool for buyers," European Journal of Operational Research, Elsevier, vol. 90(1), pages 142-155, April.
    2. Mikhailov, L., 2002. "Fuzzy analytical approach to partnership selection in formation of virtual enterprises," Omega, Elsevier, vol. 30(5), pages 393-401, October.
    3. Hau L. Lee, 1992. "Lot Sizing to Reduce Capacity Utilization in a Production Process with Defective Items, Process Corrections, and Rework," Management Science, INFORMS, vol. 38(9), pages 1314-1328, September.
    4. Van Nieuwenhuyse, Inneke & Vandaele, Nico, 2006. "The impact of delivery lot splitting on delivery reliability in a two-stage supply chain," International Journal of Production Economics, Elsevier, vol. 104(2), pages 694-708, December.
    5. Meade, L. M. & Liles, D. H. & Sarkis, J., 1997. "Justifying strategic alliances and partnering: a prerequisite for virtual enterprising," Omega, Elsevier, vol. 25(1), pages 29-42, February.
    6. Talluri, Srinivas & Baker, R. C. & Sarkis, Joseph, 1999. "A framework for designing efficient value chain networks," International Journal of Production Economics, Elsevier, vol. 62(1-2), pages 133-144, May.
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    Cited by:

    1. repec:wsi:apjorx:v:34:y:2017:i:02:n:s0217595917500087 is not listed on IDEAS
    2. Baghalian, Atefeh & Rezapour, Shabnam & Farahani, Reza Zanjirani, 2013. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case," European Journal of Operational Research, Elsevier, vol. 227(1), pages 199-215.
    3. Farahani, Reza Zanjirani & Rezapour, Shabnam & Drezner, Tammy & Fallah, Samira, 2014. "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications," Omega, Elsevier, vol. 45(C), pages 92-118.
    4. Emerson, Denise & Zhou, Wei & Piramuthu, Selwyn, 2009. "Goodwill, inventory penalty, and adaptive supply chain management," European Journal of Operational Research, Elsevier, vol. 199(1), pages 130-138, November.


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