Optimization of the Collaborative Hub Location Problem with Metaheuristics

By creating new job opportunities and developing the regional economy, the transport of goods generates significant costs, environmental and sanitary nuisances, and high greenhouse gas (GHG) emissions. In this context, collaboration is an interesting solution that can be used to enable companies to...

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Autores principales:	Mohamed Amine Gargouri, Nadia Hamani, Nassim Mrabti, Lyes Kermad
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	distribution network design problem hub location problem collaboration sustainability metaheuristic mixed integer linear programming Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/6cf9ada8926d4d8d8a38af0e7113b696
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spelling	oai:doaj.org-article:6cf9ada8926d4d8d8a38af0e7113b6962021-11-11T18:18:17ZOptimization of the Collaborative Hub Location Problem with Metaheuristics10.3390/math92127592227-7390https://doaj.org/article/6cf9ada8926d4d8d8a38af0e7113b6962021-10-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/21/2759https://doaj.org/toc/2227-7390By creating new job opportunities and developing the regional economy, the transport of goods generates significant costs, environmental and sanitary nuisances, and high greenhouse gas (GHG) emissions. In this context, collaboration is an interesting solution that can be used to enable companies to overcome some problems such as globalization, economic crisis, health crisis, issues related to sustainability, etc. This study deals with the design of a multiperiod multiproduct three-echelon collaborative distribution network with a heterogeneous fleet. By applying the mixed integer linear problem (MILP) formulations, it was possible to study the three dimensions of sustainability (economic, environmental, and social/societal). Since the examined problem was NP-hard, it was solved using four metaheuristic approaches to minimize the different logistics costs or CO<sub>2</sub> emissions. The social/societal aspect evaluated the accident rate and the noise level generated by the freight transport. Four algorithms were developed to achieve our objectives: a genetic algorithm, a simulated annealing, a particle swarm algorithm, and a vibration damping optimization algorithm. Considering a French distribution network, these algorithms overcame the limits of the exact solution method by obtaining optimal solutions with reasonable execution time.Mohamed Amine GargouriNadia HamaniNassim MrabtiLyes KermadMDPI AGarticledistribution network design problemhub location problemcollaborationsustainabilitymetaheuristicmixed integer linear programmingMathematicsQA1-939ENMathematics, Vol 9, Iss 2759, p 2759 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	distribution network design problem hub location problem collaboration sustainability metaheuristic mixed integer linear programming Mathematics QA1-939
spellingShingle	distribution network design problem hub location problem collaboration sustainability metaheuristic mixed integer linear programming Mathematics QA1-939 Mohamed Amine Gargouri Nadia Hamani Nassim Mrabti Lyes Kermad Optimization of the Collaborative Hub Location Problem with Metaheuristics
description	By creating new job opportunities and developing the regional economy, the transport of goods generates significant costs, environmental and sanitary nuisances, and high greenhouse gas (GHG) emissions. In this context, collaboration is an interesting solution that can be used to enable companies to overcome some problems such as globalization, economic crisis, health crisis, issues related to sustainability, etc. This study deals with the design of a multiperiod multiproduct three-echelon collaborative distribution network with a heterogeneous fleet. By applying the mixed integer linear problem (MILP) formulations, it was possible to study the three dimensions of sustainability (economic, environmental, and social/societal). Since the examined problem was NP-hard, it was solved using four metaheuristic approaches to minimize the different logistics costs or CO<sub>2</sub> emissions. The social/societal aspect evaluated the accident rate and the noise level generated by the freight transport. Four algorithms were developed to achieve our objectives: a genetic algorithm, a simulated annealing, a particle swarm algorithm, and a vibration damping optimization algorithm. Considering a French distribution network, these algorithms overcame the limits of the exact solution method by obtaining optimal solutions with reasonable execution time.
format	article
author	Mohamed Amine Gargouri Nadia Hamani Nassim Mrabti Lyes Kermad
author_facet	Mohamed Amine Gargouri Nadia Hamani Nassim Mrabti Lyes Kermad
author_sort	Mohamed Amine Gargouri
title	Optimization of the Collaborative Hub Location Problem with Metaheuristics
title_short	Optimization of the Collaborative Hub Location Problem with Metaheuristics
title_full	Optimization of the Collaborative Hub Location Problem with Metaheuristics
title_fullStr	Optimization of the Collaborative Hub Location Problem with Metaheuristics
title_full_unstemmed	Optimization of the Collaborative Hub Location Problem with Metaheuristics
title_sort	optimization of the collaborative hub location problem with metaheuristics
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/6cf9ada8926d4d8d8a38af0e7113b696
work_keys_str_mv	AT mohamedaminegargouri optimizationofthecollaborativehublocationproblemwithmetaheuristics AT nadiahamani optimizationofthecollaborativehublocationproblemwithmetaheuristics AT nassimmrabti optimizationofthecollaborativehublocationproblemwithmetaheuristics AT lyeskermad optimizationofthecollaborativehublocationproblemwithmetaheuristics
_version_	1718431891188613120

Optimization of the Collaborative Hub Location Problem with Metaheuristics

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