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A hybrid biogeography-based optimization algorithm for three-dimensional bin size designing and packing problem
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DOI：10.1016/j.cie.2023.109239.png)
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Abstract
En 中文
The three-dimensional bin packing problem (3D-BPP) plays a critical role in logistics activities. Prior studies focus on 3D-BPP in cases where bin size is predetermined. However, bin volume utilization can be improved significantly by optimizing bin size. In this study, we propose a novel three-dimensional bin size designing and packing problem (3D-BSDPP) and a hybrid biogeography-based optimization (HBBO) algorithm to address the problem by maximizing bin volume utilization by optimizing the bin size. The HBBO combines a differential evolution algorithm with basic biogeography-based optimization to improve exploration ability, and a novel local search strategy involving three specific local search operators is proposed to accelerate the HBBO convergence. Finally, a novel heuristic packing method is employed to find a high-quality packing solution. The proposed algorithm is evaluated through experiments carried out on a practical bin packing application. The results indicate that the proposed algorithm outperforms existing algorithms in solving the 3D-BSDPP.
Keywords:
Three-dimensional bin size designing and
packing problem
Hybrid biogeography -based optimization
Differential evolution
Packing method
Journal
IF:
6.5
Papers:
1.0W
Citations:
3.8W