Abstract:

Bin packing problem (BPP) is a combinatorial NP-hard problem that has variations including one, two and three dimensional packing, variable sized packing and packing with constraints. In the literature, exact and approximation algorithms have been mostly used to solve bin packing problems. Genetic Algorithms are meta-heuristic methods that have been applied to a vast majority of well-known optimization problems including the bin packing problems. In this paper, a variant of bin-packing problem for variable bins is addressed. The capacity constraints including volume and weight are given; moreover, to avoid item conflicts is defined as an additional constraint. A decision support model utilizing the genetic algorithm is introduced for this variant of the BPP. The performance of the model is tested with sample input, the results obtained are presented and discussed in the results section.

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