Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications

The bin-packing problem (BPP) is an age-old NP-hard combinatorial optimization problem, which is defined as the placement of a set of different-sized items into identical bins such that the number of containers used is optimally minimized. Besides, different variations of the problem do exist in pra...

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Autores principales:	Munien Chanaleä, Ezugwu Absalom E.
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	bin-packing problem one-dimensional nature-inspired metaheuristic Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/88c9fcae61b14dd6a4799716260dacce
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id	oai:doaj.org-article:88c9fcae61b14dd6a4799716260dacce
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spelling	oai:doaj.org-article:88c9fcae61b14dd6a4799716260dacce2021-12-05T14:10:51ZMetaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications2191-026X10.1515/jisys-2020-0117https://doaj.org/article/88c9fcae61b14dd6a4799716260dacce2021-04-01T00:00:00Zhttps://doi.org/10.1515/jisys-2020-0117https://doaj.org/toc/2191-026XThe bin-packing problem (BPP) is an age-old NP-hard combinatorial optimization problem, which is defined as the placement of a set of different-sized items into identical bins such that the number of containers used is optimally minimized. Besides, different variations of the problem do exist in practice depending on the bins dimension, placement constraints, and priority. More so, there are several important real-world applications of the BPP, especially in cutting industries, transportation, warehousing, and supply chain management. Due to the practical relevance of this problem, researchers are consistently investigating new and improved techniques to solve the problem optimally. Nature-inspired metaheuristics are powerful algorithms that have proven their incredible capability of solving challenging and complex optimization problems, including several variants of BPPs. However, no comprehensive literature review exists on the applications of the metaheuristic approaches to solve the BPPs. Therefore, to fill this gap, this article presents a survey of the recent advances achieved for the one-dimensional BPP, with specific emphasis on population-based metaheuristic algorithms. We believe that this article can serve as a reference guide for researchers to explore and develop more robust state-of-the-art metaheuristics algorithms for solving the emerging variants of the bin-parking problems.Munien ChanaleäEzugwu Absalom E.De Gruyterarticlebin-packing problemone-dimensionalnature-inspiredmetaheuristicScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 636-663 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	bin-packing problem one-dimensional nature-inspired metaheuristic Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	bin-packing problem one-dimensional nature-inspired metaheuristic Science Q Electronic computers. Computer science QA75.5-76.95 Munien Chanaleä Ezugwu Absalom E. Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications
description	The bin-packing problem (BPP) is an age-old NP-hard combinatorial optimization problem, which is defined as the placement of a set of different-sized items into identical bins such that the number of containers used is optimally minimized. Besides, different variations of the problem do exist in practice depending on the bins dimension, placement constraints, and priority. More so, there are several important real-world applications of the BPP, especially in cutting industries, transportation, warehousing, and supply chain management. Due to the practical relevance of this problem, researchers are consistently investigating new and improved techniques to solve the problem optimally. Nature-inspired metaheuristics are powerful algorithms that have proven their incredible capability of solving challenging and complex optimization problems, including several variants of BPPs. However, no comprehensive literature review exists on the applications of the metaheuristic approaches to solve the BPPs. Therefore, to fill this gap, this article presents a survey of the recent advances achieved for the one-dimensional BPP, with specific emphasis on population-based metaheuristic algorithms. We believe that this article can serve as a reference guide for researchers to explore and develop more robust state-of-the-art metaheuristics algorithms for solving the emerging variants of the bin-parking problems.
format	article
author	Munien Chanaleä Ezugwu Absalom E.
author_facet	Munien Chanaleä Ezugwu Absalom E.
author_sort	Munien Chanaleä
title	Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications
title_short	Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications
title_full	Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications
title_fullStr	Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications
title_full_unstemmed	Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications
title_sort	metaheuristic algorithms for one-dimensional bin-packing problems: a survey of recent advances and applications
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/88c9fcae61b14dd6a4799716260dacce
work_keys_str_mv	AT munienchanalea metaheuristicalgorithmsforonedimensionalbinpackingproblemsasurveyofrecentadvancesandapplications AT ezugwuabsalome metaheuristicalgorithmsforonedimensionalbinpackingproblemsasurveyofrecentadvancesandapplications
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Metaheuristic algorithms for one-dimensional bin-packing problems: A survey of recent advances and applications

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