A pattern-based algorithm with fuzzy logic bin selector for online bin packing problem

Lin, Bingchen; Li, Jiawei; Cui, Tianxiang; Jin, Huan; Bai, Ruibin; Qu, Rong; Garibaldi, Jon

Abstract

The online bin packing problem is a well-known optimization challenge that finds application in a wide range of real-world scenarios. In the paper, we propose a novel algorithm called FuzzyPatternPack(FPP), which leverages fuzzy inference and pattern-based predictions of the distribution of item sizes in online bin packing. In comparison to traditional heuristics like BestFit(BF) and FirstFit(FF), as well as the more recent PatternPack(PaP) and ProfilePacking(PrP) algorithm based on online predictions, FPP demonstrates competitive and superior performance in solving various benchmark problems. Particularly, it excels in addressing problems with evolving distributions, making it a promising solution for real-world applications where the item sizes may change over time. This research unveils the promising potential of employing fuzzy logic to effectively address uncertainty in scheduling and planning problems.

Citation

Lin, B., Li, J., Cui, T., Jin, H., Bai, R., Qu, R., & Garibaldi, J. (2024). A pattern-based algorithm with fuzzy logic bin selector for online bin packing problem. Expert Systems with Applications, 249, Article 123515. https://doi.org/10.1016/j.eswa.2024.123515

• Journal Article Type: Article
• Acceptance Date: Feb 16, 2024
• Online Publication Date: Feb 17, 2024
• Publication Date: Sep 1, 2024
• Deposit Date: Apr 2, 2024
• Publicly Available Date: Apr 2, 2024
• Journal: Expert Systems with Applications
• Print ISSN: 0957-4174
• Electronic ISSN: 0957-4174
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 249
• Article Number: 123515
• DOI: https://doi.org/10.1016/j.eswa.2024.123515
• Keywords: Online bin packing Planning under uncertainty Learning for planning and scheduling; Fuzzy logic; Pattern-based planning
• Public URL: https://nottingham-repository.worktribe.com/output/31619007
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0957417424003804?via%3Dihub