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A Histogram-Matching Approach to the Evolution of Bin-Packing Strategies

, , und . 2007 IEEE Congress on Evolutionary Computation, Seite 3500--3507. Singapore, IEEE Computational Intelligence Society, IEEE Press, (25-28 September 2007)

Zusammenfassung

We present a novel algorithm for the one-dimension offline bin packing problem with discrete item sizes based on the notion of matching the item-size histogram with the bin-gap histogram. The approach is controlled by a constructive heuristic function which decides how to prioritise items in order to minimise the difference between histograms. We evolve such a function using a form of linear register-based genetic programming system. We test our evolved heuristics and compare them with hand-designed ones, including the well known best fit decreasing heuristic. The evolved heuristics are human-competitive, generally being able to outperform high performance human-designed heuristics.

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