Efficient Hybrid Grouping Heuristics for the Bin Packing Problem

Laura Cruz-Reyes, Marcela Quiroz C., Adriana C. F. Alvim, Héctor J. Fraire Huacuja, Claudia Gómez S., José Torres-Jiménez


This article addresses a classical problem known for its applicability and complexity: the Bin Packing Problem (BPP). A hybrid grouping genetic algorithm called HGGA-BP is proposed to solve BPP. The proposed algorithm is inspired by the Falkenauer grouping encoding scheme, which applies evolutionary operators at the bin level. HGGA-BP includes efficient heuristics to generate the initial population and performs mutation and crossover for groups as well as hybrid strategies for the arrangement of objects that were released by the group operators. The effectiveness of the algorithm is comparable with the best state-of-the-art algorithms, outperforming the published results for the class of instances hard28, which has shown the highest difficulty for algorithms that solve BPP


Computer methodologies; artificial intelligence; problem solving; bin packing problem; hybrid genetic algorithm.

Full Text: PDF (Spanish)