Space defragmentation for packing problems

Wenbin Zhu, Zhaoyi Zhang, Wee-Chong Oon and Andrew Lim

European Journal of Operational Research, 2012, vol. 222, issue 3, 452-463

Abstract: One of main difficulties of multi-dimensional packing problems is the fragmentation of free space into several unusable small parts after a few items are packed. This study proposes a defragmentation technique to combine the fragmented space into a continuous usable space, which potentially allows the packing of additional items. We illustrate the effectiveness of this technique using the two- and three-dimensional bin packing problem, where the aim is to load all given items (represented by rectangular boxes) into the minimum number of identical bins. Experimental results based on well-known 2D and 3D bin packing data sets show that our defragmentation technique alone is able to produce solutions approaching the quality of considerably more complex meta-heuristic approaches for the problem. In conjunction with a bin shuffling strategy for incremental improvement, our resultant algorithm outperforms all leading meta-heuristic approaches based on the commonly used benchmark data by a significant margin.

Keywords: Packing; 2D/3D bin packing; Space defragmentation; Bin shuffling; Comparability graph; Visibility graph (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:222:y:2012:i:3:p:452-463

DOI: 10.1016/j.ejor.2012.05.031

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