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Bi-Space Search: Optimizing the Hybridization of Search Spaces in Solving the One Dimensional Bin Packing Problem

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Artificial Intelligence and Soft Computing (ICAISC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13589))

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Abstract

Search methodologies essentially explore a solution space to solve optimization problems. As the field has developed the effectiveness of exploring other spaces has been established. For example genetic programming explores the program space. Similarly, hyper-heuristics explore the heuristic space. In previous work the advantage of switching search between different spaces rather than working in a single space has been illustrated. This paper extends this work by presenting the bi-space search which optimizes when the switch between spaces should take place. The bi-space search employs iterated local search to optimize when to switch between the solution and heuristic spaces in solving discrete optimization problems. The performance of the bi-space search is compared to searching the solution space only and a hyper-heuristic searching the heuristic space. Both the solution and heuristic space searches employ iterated local search to explore the solution and heuristic space respectively. All three searches are evaluated on the one dimensional bin packing problem. The bi-space search was found to outperform the solution space search and hyper-heuristic.

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Notes

  1. 1.

    http://or.dei.unibo.it/library/bpplib.

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Acknowledgements

This work was funded as part of the Multichoice Research Chair in Machine Learning at the University of Pretoria, South Africa. The authors acknowledge the Centre for High Performance Computing (CHPC), South Africa, for providing computational resources toward this research.

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Authors and Affiliations

  1. University of Pretoria, Pretoria, South Africa

    Derrick Beckedahl & Nelishia Pillay

Authors
  1. Derrick Beckedahl
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  2. Nelishia Pillay
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Corresponding author

Correspondence to Derrick Beckedahl .

Editor information

Editors and Affiliations

  1. Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Beckedahl, D., Pillay, N. (2023). Bi-Space Search: Optimizing the Hybridization of Search Spaces in Solving the One Dimensional Bin Packing Problem. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2022. Lecture Notes in Computer Science(), vol 13589. Springer, Cham. https://doi.org/10.1007/978-3-031-23480-4_17

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  • DOI: https://doi.org/10.1007/978-3-031-23480-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23479-8

  • Online ISBN: 978-3-031-23480-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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