μ𝜃-EGF: A New Multi-Thread and Nature-Inspired Algorithm for the Packing Problem

In this paper, the authors present a new algorithm efficient solution to the packing problem in two dimensions. The authors propose a new heuristic using the value of the electromagnetic field to determine the best position to place a circular object in a configuration of other circular objects prev...

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Bibliographic Details
Published in:Mobile networks and applications Vol. 25; no. 6; pp. 2105 - 2117
Main Authors: Martinez-Rios, Felix, Marmolejo-Saucedo, Jose A., García-Jacas, César R., Murillo-Suarez, Alfonso
Format: Journal Article
Language:English
Published: New York Springer US 01.12.2020
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ISSN:1383-469X, 1572-8153
Online Access:Get full text
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Summary:In this paper, the authors present a new algorithm efficient solution to the packing problem in two dimensions. The authors propose a new heuristic using the value of the electromagnetic field to determine the best position to place a circular object in a configuration of other circular objects previously packed. Also, this algorithm simulates two processes to compact objects already placed, inspired by gravitational forces, to minimize the empty space in the container and maximizing the number of objects in the container. To determine the efficacy of this algorithm, the authors carried out experiments with twenty-four instances. Parallel computing can contribute to making decision processes such as optimization and prediction more agile and faster. Real-time decision making involves the use of solution methodologies and algorithms. For this reason the present manuscript shows an alternative for the solution of a classic industry problem that must be solved quickly. Packaging optimization can help reduce waste of container material. The material used to transport the products can reduce its environmental impact due to an efficient packaging process. Light-weighting can also be accomplished by reducing the amount of packaging material used.
ISSN:1383-469X
1572-8153
DOI:10.1007/s11036-020-01558-8