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A hybrid algorithm based on variable neighbourhood for the strip packing problem

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Abstract

This paper addresses the strip packing problem, which has a wide range of real-world applications. Our proposed algorithm is a hybrid metaheuristic that combines an improved heuristic algorithm with a variable neighbourhood search. Different neighbourhoods are constructed based on the concept of block patterns. The proposed algorithm has three interesting features. First, a least-waste strategy is used to improve the constructive heuristics. Second, a better sorting sequence is selected to generate an initial solution. Finally, different neighbourhoods are constructed based on block patterns. The computational results from a diverse set of problem instances show that the proposed algorithm performs better than algorithms reported in the literature for most of the problem sets compared.

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Acknowledgments

Defu Zhang would like to thank his supervisor Prof. Wenqi Huang who taught him a great deal about research. This work was in memory of Prof. Wenqi Huang and was partially supported by the National Nature Science Foundation of China (Grant no. 61272003), Research Committee of University of Macau (MYRG041(Y1-L1)- FST13-SYW) and a grant from City University of Hong Kong (Project No. 7004149). The authors would like to thank the reviewers for their valuable comments that help improve this paper.

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Authors and Affiliations

  1. Department of Computer Science, Xiamen University, Xiamen, China

    Defu Zhang, Yuxin Che & Furong Ye

  2. Department of Computer and Information Science, University of Macau, Macau, China

    Yain-Whar Si

  3. Faculty of Engineering, The University of Hong Kong, Hong Kong, China

    Stephen C. H. Leung

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  1. Defu Zhang
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  2. Yuxin Che
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  3. Furong Ye
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  4. Yain-Whar Si
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  5. Stephen C. H. Leung
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Correspondence to Defu Zhang.

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Zhang, D., Che, Y., Ye, F. et al. A hybrid algorithm based on variable neighbourhood for the strip packing problem. J Comb Optim 32, 513–530 (2016). https://doi.org/10.1007/s10878-016-0036-6

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  • DOI: https://doi.org/10.1007/s10878-016-0036-6

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