Abstract
This paper introduces a new tabu search algorithm for a strip packing problem. It integrates several key features: A consistent neighborhood, a fitness function including problem knowledge, and a diversification based on the history of the search. The neighborhood only considers valid, sometimes partial, packings. The fitness function incorporates measures related to the empty spaces. Diversification relies on a set of historically “frozen” objects. Experimental results are shown on a set of well-known hard instances and compared with previously reported tabu search algorithms as well as the best performing algorithms.
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Gómez-Villouta, G., Hamiez, JP., Hao, JK. (2010). Tabu Search with Consistent Neighbourhood for Strip Packing. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13022-9_1
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DOI: https://doi.org/10.1007/978-3-642-13022-9_1
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