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Single and multi-objective genetic algorithms for the container loading problem

Authors:

Gara Miranda,

Algirdas Lančinskas,

Yanira GonzálezAuthors Info & Claims

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 291 - 292

https://doi.org/10.1145/3067695.3076085

Published: 15 July 2017 Publication History

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Abstract

Container Loading Problems (CLPs) deal with determination of the optimal pattern for packing boxes into a given container usually with respect to the maximal utilization of the total container volume. On the other hand, it is also important to maximize the utilization of the maximal container weight for which is paid when buying a shipment service. In this paper we analyze two genetic algorithms specially adopted to solve CLP. One of them is based on the Genetic Algorithm (GA) and is suitable to solve single-objective CLPs, while another one is based on the Non-dominated Sorting Genetic Algorithm (NSGA-II), suitable for solution of CLP by simultaneously considering both of the above mentioned objectives. The algorithms have been experimentally investigated by solving various CLP instances of different complexity. The obtained results showed that simultaneous consideration of both objectives using the proposed multi-objective optimization algorithm gives better results in utilization of container volume when solving complex CLP instances.

References

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Andreas Bortfeldt and Gerhard Wáscher. 2012. Container Loading Problems - A State-of-the-Art Review. Working Paper 1. Otto-von-Guericke-Universität Magdeburg.

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Jesica de Armas, Yanira González, Gara Miranda, and Coromoto León. 2012. Parallelization of the Multi-Objective Container Loading Problem. In IEEE World Congress on Computational Intelligence (WCCI). Brisbane, Australia, 155--162.

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K. Deb, S. Agrawal, A. Pratab, and T. Meyarivan. 2000. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. In VI Conference on Parallel Problem Solving from Nature (LNCS), Vol. 1917. Springer, 849--858.

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Yanira González, Gara Miranda, and Coromoto León. 2013. A Multi-level Filling Heuristic for the Multi-objective Container Loading Problem. In International Joint Conference SOCO'13-CISIS'13-ICEUTE'13. Springer International Publishing, 11--20.

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Yanira González, Gara Miranda, and Coromoto León. 2016. An Instance Generator for the Multi-Objective 3D Packing Problem. In International Joint Conference SOCO'16-CISIS'16-ICEUTE'16. Springer International Publishing, 386--396.

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Kuo RHo PZulvia F(2023)Application of metaheuristics algorithm on a multi-objective container loading problem considering container’s utilization and vehicle’s balanceApplied Soft Computing10.1016/j.asoc.2023.110417143(110417)Online publication date: Aug-2023
https://doi.org/10.1016/j.asoc.2023.110417

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Single and multi-objective genetic algorithms for the container loading problem

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GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2017

1934 pages

ISBN:9781450349390

DOI:10.1145/3067695

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 15 July 2017

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SIGEVO

GECCO '17: Genetic and Evolutionary Computation Conference

July 15 - 19, 2017

Berlin, Germany

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Kuo RHo PZulvia F(2023)Application of metaheuristics algorithm on a multi-objective container loading problem considering container’s utilization and vehicle’s balanceApplied Soft Computing10.1016/j.asoc.2023.110417143(110417)Online publication date: Aug-2023
https://doi.org/10.1016/j.asoc.2023.110417

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Evolutionary algorithms and multi-objectivization for the travelling salesman problem

Multi-objective multi-population biased random-key genetic algorithm for the 3-D container loading problem

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Evolutionary algorithms and multi-objectivization for the travelling salesman problem

Multi-objective multi-population biased random-key genetic algorithm for the 3-D container loading problem

Implementation and comparison of algorithms for multi-objective optimization based on genetic algorithms applied to the management of an automated warehouse

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