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Multi-product Supply Planning for Combat Units in Battlefield Environment

In: The 19th International Conference on Industrial Engineering and Engineering Management

Author

Listed:
  • Ji Ren

    (National University of Defense Technology)

  • Xiao-lei Zheng

    (Lagistic Command College)

  • Yue-jin Tan

    (National University of Defense Technology)

Abstract

The multi-product supply planning problem is investigated in the battlefield environment. The practical quantity of the products consumed by the combat units is stochastic, while the supplying process is also uncertain because of the random loss caused by attacks from the enemy. A nonlinear programming model is proposed to optimize the problem with both uncertain demand and supply consideration, and a solution algorithm based on Lagrangian relaxation is developed to obtain the optimal solution. Randomly generated examples involving 10, 100 and 1,000 commodities respectively are solved by the proposed algorithm. The computational performance of the algorithm is analyzed, which shows that the proposed algorithm can obtain optimal solutions for all examples with different sizes in short time.

Suggested Citation

  • Ji Ren & Xiao-lei Zheng & Yue-jin Tan, 2013. "Multi-product Supply Planning for Combat Units in Battlefield Environment," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), The 19th International Conference on Industrial Engineering and Engineering Management, edition 127, chapter 0, pages 445-453, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-37270-4_43
    DOI: 10.1007/978-3-642-37270-4_43
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    Cited by:

    1. Mohammad Marufuzzaman & Farjana Nur & Amy E. Bednar & Mark Cowan, 2020. "Enhancing Benders decomposition algorithm to solve a combat logistics problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 161-198, March.

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