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Distributed supply chain management using ant colony optimization

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  • Silva, C.A.
  • Sousa, J.M.C.
  • Runkler, T.A.
  • Sá da Costa, J.M.G.

Abstract

Successful supply chain management requires a cooperative integration between all the partners in the network. At the operational level, the partners individual behavior should be optimal and therefore their activities have to be planned using sophisticated optimization tools. However, these tools should take into account the planning of the remaining partners, through the exchange of information, in order to allow some kind of cooperation between the elements of the chain. This paper introduces a new supply chain management technique, based on modeling a generic supply chain with suppliers, logistics and distributers, as a distributed optimization problem. The different operational activities are solved by the optimization meta-heuristic called ant colony optimization, which allows the exchange of information between different optimization problems by means of a pheromone matrix. The simulation results show that the new methodology is more efficient than a simple decentralized methodology for different instances of a supply chain.

Suggested Citation

  • Silva, C.A. & Sousa, J.M.C. & Runkler, T.A. & Sá da Costa, J.M.G., 2009. "Distributed supply chain management using ant colony optimization," European Journal of Operational Research, Elsevier, vol. 199(2), pages 349-358, December.
    • Handle: RePEc:eee:ejores:v:199:y:2009:i:2:p:349-358
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    References listed on IDEAS

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    2. Benoit Montreuil & Caroline Cloutier & Olivier Labarthe & Jonathan Loubier, 2015. "Holistic modelling, simulation and visualisation of demand and supply chains," International Journal of Business Performance and Supply Chain Modelling, Inderscience Enterprises Ltd, vol. 7(1), pages 53-70.
    3. Seyyed-Alireza Radmanesh & Alireza Haji & Omid Fatahi Valilai, 2023. "Blockchain-Based Architecture for a Sustainable Supply Chain in Cloud Architecture," Sustainability, MDPI, vol. 15(11), pages 1-19, June.
    4. Hämäläinen, Raimo P. & Luoma, Jukka & Saarinen, Esa, 2013. "On the importance of behavioral operational research: The case of understanding and communicating about dynamic systems," European Journal of Operational Research, Elsevier, vol. 228(3), pages 623-634.
    5. Lau, Kwok Hung, 2013. "Measuring distribution efficiency of a retail network through data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 146(2), pages 598-611.
    6. Gregorio Rius-Sorolla & Julien Maheut & Sofia Estelles-Miguel & Jose P. Garcia-Sabater, 2021. "Collaborative Distributed Planning with Asymmetric Information. A Technological Driver for Sustainable Development," Sustainability, MDPI, vol. 13(12), pages 1-23, June.

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