A hybrid 'bee(s) algorithm' for solving container loading problems
Applied Soft Computing
A parallel multi-population biased random-key genetic algorithm for a container loading problem
Computers and Operations Research
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This paper presents a new heuristic algorithm for solving the single-container loading problem. The algorithm is to formalize human experience formed in the last 1000 years by modern mathematical tools, and to refine it by a new observation. Its key issue is the cavity degree of an action that packs an item into a layer of the container, such that the item is packed as compactly as possible to other items already packed in the same layer. For the 1500 well-known benchmark problems from Bischoff, Ratcliff, and Davies, the new algorithm achieves an average container volume utilization of 89.59% with a reasonable average computing time of 27.78 min. This improves the current best utilization record reported in the literature considerably by 0.62%. Of those 1500, for the 800 strongly heterogeneous problems especially, where other algorithms usually achieved lower utilizations, it achieves an average volume utilization of 89.77%, which breaks the current best record markedly by 2.08%.