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A bi-criteria hybrid metaheuristic for analysing an integrated automotive supply chain

Author

Listed:
  • Sherif A Masoud

    (WestRock, Duluth, USA)

  • Scott J Mason

    (Clemson University, Clemson, USA)

Abstract

The automotive industry is one of the most important manufacturing sectors in the world due to its economic impact and technological complexities. While supply chain performance can have a dramatic impact on the automotive industry, there are multiple, often conflicting objectives that typically are used to optimize performance. We model the trade-off between cost and service level, and present a bi-criteria heuristic optimization methodology for a two-stage, integrated automotive supply chain. Our problem contains sequence-dependent setups on parallel machines and auxiliary resource assignments. We minimize the total cost of setups, inventory holding, and transportation costs, and the maximum percentage of outsourced parts per customer, simultaneously. We use our proposed method to solve a set of problem instances that are based on industrial data. Our proposed method generates approximate Pareto (efficient) solutions in a timely manner for use in practice.

Suggested Citation

  • Sherif A Masoud & Scott J Mason, 2016. "A bi-criteria hybrid metaheuristic for analysing an integrated automotive supply chain," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(3), pages 516-526, March.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:3:p:516-526
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    Cited by:

    1. Martina Bris Alic, 2023. "The Optimization Methods In Supply Chain Management – A Bibliometric Analysis," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 23, pages 281-296.

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