Theoretical Paper

Journal of the Operational Research Society (2008) 59, 823–832; doi:10.1057/palgrave.jors.2602393 Published online 4 April 2007

One-dimensional heuristics adapted for two-dimensional rectangular strip packing

G Belov1, G Scheithauer1 and E A Mukhacheva2

  1. 1Technische Universität Dresden, Dresden, Germany
  2. 2Ufa State Aviation Technical University, Ufa, Russia

Correspondence: G Belov, Institute of Numeral Mathematics, Technische Universität Dresden, 01062 Dresden, Germany. E-mail: bg32767@gmx.net

Received January 2006; Accepted November 2006; Published online 4 April 2007.

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Abstract

We consider two-dimensional rectangular strip packing without rotation of items and without the guillotine cutting constraint. We propose two iterative heuristics. The first one, SVC(SubKP), is based on a single-pass heuristic SubKP which fills every most bottom-left free space in a one-dimensional knapsack fashion, that is, considering only item widths. It appears especially important to assign suitable 'pseudo-profits' in this knapsack problem. The second heuristic BS(BLR) is based on the known randomized framework Bubble-Search. It generates different item sequences and runs a new sequence-based heuristic Bottom-Left-Right (BLR), a simple modification of the Bottom-Left heuristic. We investigate the solution sets of SubKP and BLR and their relation to each other. In the tests, SVC(SubKP) improves the results for larger instances of the waste-free classes of Hopper and Turton and, on average, for the tested non-waste-free classes, compared to the latest literature. BS(BLR) gives the best results in some classes with smaller number of items (20,40).

Keywords:

strip packing, heuristics, greedy, stochastic search, knapsack

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