Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/28921
Title: A Taboo-Search Algorithm for 3D-Binpacking Problem in Containers
Author: Leon, Paul
Cueva, Rony
Tupia, Manuel
Paiva Dias, Gonçalo
Keywords: Bin packing problem
Taboo search
Genetic algorithm
Metaheuristic
Issue Date: 2019
Abstract: One of the biggest challenges facing by logistics companies is the packing of fragile products in containers. These activities, due to the nature of the packaged products, can entail great risks for the company due to the possible losses and the cost of the transporting containers, so-called in literature as binpacking problem. Being this problem of a complex computational nature (NPhard), companies do not have exact technological solutions to establish a positional sequence of the packages that have to be arranged in containers, considering aspects such as fragility, weight, volume, among other aspects. In most cases only the volume and order of dispatch is considered. The application of bio-inspired techniques such as metaheuristics are an appropriate way to obtain approximate solutions to this kind of problems, without the difficulties of complex software implementations. In previous works of the authors, bioinspired algorithms have been developed to solve the problem and in this paper a taboo-search algorithm is proposed to solve the 3D-bin packing variant, which has been compared with the previous algorithms obtaining approximately a waste reduction of 28%. Fundamentally, research has used real data from Peruvian ceramic industry.
Peer review: yes
URI: http://hdl.handle.net/10773/28921
DOI: 10.1007/978-3-030-16181-1_22
Appears in Collections:ESTGA - Comunicações
GOVCOPP - Comunicações

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