An Analogy between Bin Packing Problem and Permutation Problem: A New Encoding Scheme

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Abstract

The bin packing problem aims to pack a set of items in a minimum number of bins, with respect to the size of the items and capacity of the bins. This is an NP-hard problem. Several approach methods have been developed to solve this problem. In this paper, we propose a new encoding scheme which is used in a hybrid resolution: a metaheuristic is matched with a list algorithm (Next Fit, First Fit, Best Fit) to solve the bin packing problem. Any metaheuristic can be used but in this paper, our proposition is implemented on a single solution based metaheuristic (stochastic descent, simulated annealing, kangaroo algorithm). This hybrid method is tested on literature instances to ensure its good results. © IFIP International Federation for Information Processing 2014.

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Gourgand, M., Grangeon, N., & Klement, N. (2014). An Analogy between Bin Packing Problem and Permutation Problem: A New Encoding Scheme. In IFIP Advances in Information and Communication Technology (Vol. 438, pp. 572–579). Springer New York LLC. https://doi.org/10.1007/978-3-662-44739-0_70

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