A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem

The pigeon-inspired optimization algorithm is a category of a newly proposed swarm intelligence-based algorithm that belongs to the population-based solution technique. The MKP is a class of complex optimization problems that have many practical applications in the fields of engineering and sciences...

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Autores principales:	Bolaji Asaju La’aro, Okwonu Friday Zinzendoff, Shola Peter Bamidele, Balogun Babatunde Sulaiman, Adubisi Obinna Damian
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2020
Materias:	pigeon-inspired optimization multidimensional knapsack problem crossover mechanism nature-inspired algorithm population-based metaheuristic Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/fc60c2b9c841491285bbdc7b165c816d
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id	oai:doaj.org-article:fc60c2b9c841491285bbdc7b165c816d
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spelling	oai:doaj.org-article:fc60c2b9c841491285bbdc7b165c816d2021-12-05T14:10:51ZA Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem2191-026X10.1515/jisys-2018-0450https://doaj.org/article/fc60c2b9c841491285bbdc7b165c816d2020-07-01T00:00:00Zhttps://doi.org/10.1515/jisys-2018-0450https://doaj.org/toc/2191-026XThe pigeon-inspired optimization algorithm is a category of a newly proposed swarm intelligence-based algorithm that belongs to the population-based solution technique. The MKP is a class of complex optimization problems that have many practical applications in the fields of engineering and sciences. Due to the practical applications of MKP, numerous algorithmic-based methods like local search and population-based search algorithms have been proposed to solve the MKP in the past few decades. This paper proposes a modified binary pigeon-inspired optimization algorithm named (Modified-BPIO) for the 0 - 1 multidimensional knapsack problem (MKP). The utilization of the binary pigeon-inspired optimization (BPIO) for solving the multidimensional knapsack problem came with huge success. However, it can be observed that the BPIO converges prematurely due to lost diversity during the search activities. Given the above, the crossover operator is integrated with the landmark component of the BPIO to improve the diversity of the solution space. The MKP benchmarks from the Operations Research (OR) library are utilized to test the performance of the proposed binary method. Experimentally, it is concluded that the proposed Modified-BPIO has a better performance when compared with the BPIO and existing state-of-the-arts that worked on the same MKP benchmarks.Bolaji Asaju La’aroOkwonu Friday ZinzendoffShola Peter BamideleBalogun Babatunde SulaimanAdubisi Obinna DamianDe Gruyterarticlepigeon-inspired optimizationmultidimensional knapsack problemcrossover mechanismnature-inspired algorithmpopulation-based metaheuristicScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 90-103 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	pigeon-inspired optimization multidimensional knapsack problem crossover mechanism nature-inspired algorithm population-based metaheuristic Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	pigeon-inspired optimization multidimensional knapsack problem crossover mechanism nature-inspired algorithm population-based metaheuristic Science Q Electronic computers. Computer science QA75.5-76.95 Bolaji Asaju La’aro Okwonu Friday Zinzendoff Shola Peter Bamidele Balogun Babatunde Sulaiman Adubisi Obinna Damian A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem
description	The pigeon-inspired optimization algorithm is a category of a newly proposed swarm intelligence-based algorithm that belongs to the population-based solution technique. The MKP is a class of complex optimization problems that have many practical applications in the fields of engineering and sciences. Due to the practical applications of MKP, numerous algorithmic-based methods like local search and population-based search algorithms have been proposed to solve the MKP in the past few decades. This paper proposes a modified binary pigeon-inspired optimization algorithm named (Modified-BPIO) for the 0 - 1 multidimensional knapsack problem (MKP). The utilization of the binary pigeon-inspired optimization (BPIO) for solving the multidimensional knapsack problem came with huge success. However, it can be observed that the BPIO converges prematurely due to lost diversity during the search activities. Given the above, the crossover operator is integrated with the landmark component of the BPIO to improve the diversity of the solution space. The MKP benchmarks from the Operations Research (OR) library are utilized to test the performance of the proposed binary method. Experimentally, it is concluded that the proposed Modified-BPIO has a better performance when compared with the BPIO and existing state-of-the-arts that worked on the same MKP benchmarks.
format	article
author	Bolaji Asaju La’aro Okwonu Friday Zinzendoff Shola Peter Bamidele Balogun Babatunde Sulaiman Adubisi Obinna Damian
author_facet	Bolaji Asaju La’aro Okwonu Friday Zinzendoff Shola Peter Bamidele Balogun Babatunde Sulaiman Adubisi Obinna Damian
author_sort	Bolaji Asaju La’aro
title	A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem
title_short	A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem
title_full	A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem
title_fullStr	A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem
title_full_unstemmed	A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem
title_sort	modified binary pigeon-inspired algorithm for solving the multi-dimensional knapsack problem
publisher	De Gruyter
publishDate	2020
url	https://doaj.org/article/fc60c2b9c841491285bbdc7b165c816d
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A Modified Binary Pigeon-Inspired Algorithm for Solving the Multi-dimensional Knapsack Problem

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