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A greedy memetic algorithm for a multiobjective dynamic bin packing problem for storing cooling objects

Author

Listed:
  • Kristina Yancey Spencer

    (Texas A&M University, 3133 TAMU)

  • Pavel V. Tsvetkov

    (Texas A&M University, 3133 TAMU)

  • Joshua J. Jarrell

    (Oak Ridge National Laboratory
    Idaho National Laboratory)

Abstract

In this paper, a multiobjective dynamic bin packing problem for storing cooling objects is introduced along with a metaheuristic designed to work well in mixed-variable environments. The dynamic bin packing problem is based on cookie production at a bakery, where cookies arrive in batches at a cooling rack with limited capacity and are packed into boxes with three competing goals. The first is to minimize the number of boxes used. The second objective is to minimize the average initial heat of each box, and the third is to minimize the maximum time until the boxes can be moved to the storefront. The metaheuristic developed here incorporated greedy heuristics into an adaptive evolutionary framework with partial decomposition into clusters of solutions for the crossover operator. The new metaheuristic was applied to a variety benchmark bin packing problems and to a small and large version of the dynamic bin packing problem. It performed as well as other metaheuristics in the benchmark problems and produced more diverse solutions in the dynamic problems. It performed better overall in the small dynamic problem, but its performance could not be proven to be better or worse in the large dynamic problem.

Suggested Citation

  • Kristina Yancey Spencer & Pavel V. Tsvetkov & Joshua J. Jarrell, 2019. "A greedy memetic algorithm for a multiobjective dynamic bin packing problem for storing cooling objects," Journal of Heuristics, Springer, vol. 25(1), pages 1-45, February.
    • Handle: RePEc:spr:joheur:v:25:y:2019:i:1:d:10.1007_s10732-018-9382-0
    DOI: 10.1007/s10732-018-9382-0
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    References listed on IDEAS

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    1. Liu, D.S. & Tan, K.C. & Huang, S.Y. & Goh, C.K. & Ho, W.K., 2008. "On solving multiobjective bin packing problems using evolutionary particle swarm optimization," European Journal of Operational Research, Elsevier, vol. 190(2), pages 357-382, October.
    2. Shoshana Anily & Julien Bramel & David Simchi-Levi, 1994. "Worst-Case Analysis of Heuristics for the Bin Packing Problem with General Cost Structures," Operations Research, INFORMS, vol. 42(2), pages 287-298, April.
    3. Silva, Elsa & Oliveira, José F. & Wäscher, Gerhard, 2014. "2DCPackGen: A problem generator for two-dimensional rectangular cutting and packing problems," European Journal of Operational Research, Elsevier, vol. 237(3), pages 846-856.
    4. Goh, C.K. & Tan, K.C. & Liu, D.S. & Chiam, S.C., 2010. "A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design," European Journal of Operational Research, Elsevier, vol. 202(1), pages 42-54, April.
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    Cited by:

    1. Manuel V. C. Vieira & Margarida Carvalho, 2023. "Lexicographic optimization for the multi-container loading problem with open dimensions for a shoe manufacturer," 4OR, Springer, vol. 21(3), pages 491-512, September.

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