Abstract
In this paper, we consider a generalization of the well-known bin packing problem, in which several types of bins are given and the number of bins of each type is limited. Unlike the classic bin packing problem, this variant is not well represented in the literature, although it has a considerable practical value. For solving this problem, a genetic algorithm is proposed. It is based on a new representation scheme that uses first fit decreasing algorithm for decoding genotypes to solutions. The computational evaluation on the test instances have shown a competitive performance of the proposed approach comparing to the heuristic algorithms previously known from the literature and Gurobi solver.
The research of the first author was funded in accordance with the state task of the IM SB RAS, project FWNF-2022-0020.
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Acknowledgement
The authors would like to thank Prof. Michele Monaci, Prof. Cristian Blum, and Dr. Ruslan Sadykov for the help with the test instances. An AMD EPYC based server of Sobolev Institute of Mathematics, Omsk Branch is used for computing.
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Borisovsky, P., Fedotova, E. (2022). Genetic Algorithm for the Variable Sized Vector Bin-Packing Problem with the Limited Number of Bins. In: Kochetov, Y., Eremeev, A., Khamisov, O., Rettieva, A. (eds) Mathematical Optimization Theory and Operations Research: Recent Trends. MOTOR 2022. Communications in Computer and Information Science, vol 1661. Springer, Cham. https://doi.org/10.1007/978-3-031-16224-4_3
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