Space defragmentation for packing problems

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

12 Scopus Citations
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Author(s)

  • Wenbin Zhu
  • Zhaoyi Zhang
  • Wee-Chong Oon
  • Andrew Lim

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)452-462
Journal / PublicationEuropean Journal of Operational Research
Volume222
Issue number3
Publication statusPublished - 1 Nov 2012

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. © 2012 Elsevier B.V. All rights reserved.

Research Area(s)

  • 2D/3D bin packing, Bin shuffling, Comparability graph, Packing, Space defragmentation, Visibility graph

Citation Format(s)

Space defragmentation for packing problems. / Zhu, Wenbin; Zhang, Zhaoyi; Oon, Wee-Chong; Lim, Andrew.

In: European Journal of Operational Research, Vol. 222, No. 3, 01.11.2012, p. 452-462.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal