Packing bins using multi-chromosomal genetic representation and better-fit heuristic

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Abstract

We propose a multi-chromosome genetic coding and set-based genetic operators for solving bin packing problem using genetic algorithm. A heuristic called better-fit is proposed, in which a left-out object replaces an existing object from a bin if it can fill the bin better. Performance of the genetic algorithm augmented with the better-fit heuristic has been compared with that of hybrid grouping genetic algorithm (HGGA). Our method has provided optimal solutions at highly reduced computational time for the benchmark uniform problem instances used. The better-fit heuristic is more effective compared to the best-fit heuristic when combined with the coding. © Springer-Verlag Berlin Heidelberg 2004.

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APA

Bhatia, A. K., & Basu, S. K. (2004). Packing bins using multi-chromosomal genetic representation and better-fit heuristic. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3316, 181–186. https://doi.org/10.1007/978-3-540-30499-9_26

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