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A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions

Industrialization and population growth have been accompanied by many problems such as waste management worldwide. Waste management and reduction have a vital role in national management. The presents study represents a multi-objective location-routing problem for hazardous wastes. The model was sol...

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Autores principales: Raeisi, Diba, Jafarzadeh Ghoushchi, Saeid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8958817/
https://www.ncbi.nlm.nih.gov/pubmed/35370360
http://dx.doi.org/10.1007/s10489-022-03334-5
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author Raeisi, Diba
Jafarzadeh Ghoushchi, Saeid
author_facet Raeisi, Diba
Jafarzadeh Ghoushchi, Saeid
author_sort Raeisi, Diba
collection PubMed
description Industrialization and population growth have been accompanied by many problems such as waste management worldwide. Waste management and reduction have a vital role in national management. The presents study represents a multi-objective location-routing problem for hazardous wastes. The model was solved using Non dominated Sorting Genetic Algorithm-II, Multi-Objective Particle Swarm Optimization, Multi-Objective Invasive Weed Optimization, Pareto Envelope-based Selection Algorithm, Multi-Objective Evolutionary Algorithm Based on Decomposition and Multi-Objective Grey Wolf Optimizer algorithms. The findings revealed that the Multi-Objective Invasive Weed Optimization algorithm was the best and the most efficient among the algorithms used in this study. Obtaining income from the incineration of the wastes and reducing the risk of COVID-19 infection are the first innovation of the present study, which considered in the presented model. The second innovation is that uncertainty was considered for some of the crucial parameters of the model while the robust fuzzy optimization model was applied. Besides, the model was solved using several meta-heuristic algorithms such as Multi-Objective Invasive Weed Optimization, Multi-Objective Evolutionary Algorithm Based on Decomposition and Multi-Objective Grey Wolf Optimizer, which were rarely used in literature. Eventually, the most efficient algorithm was identified by comparing the considered algorithms.
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spelling pubmed-89588172022-03-29 A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions Raeisi, Diba Jafarzadeh Ghoushchi, Saeid Appl Intell (Dordr) Article Industrialization and population growth have been accompanied by many problems such as waste management worldwide. Waste management and reduction have a vital role in national management. The presents study represents a multi-objective location-routing problem for hazardous wastes. The model was solved using Non dominated Sorting Genetic Algorithm-II, Multi-Objective Particle Swarm Optimization, Multi-Objective Invasive Weed Optimization, Pareto Envelope-based Selection Algorithm, Multi-Objective Evolutionary Algorithm Based on Decomposition and Multi-Objective Grey Wolf Optimizer algorithms. The findings revealed that the Multi-Objective Invasive Weed Optimization algorithm was the best and the most efficient among the algorithms used in this study. Obtaining income from the incineration of the wastes and reducing the risk of COVID-19 infection are the first innovation of the present study, which considered in the presented model. The second innovation is that uncertainty was considered for some of the crucial parameters of the model while the robust fuzzy optimization model was applied. Besides, the model was solved using several meta-heuristic algorithms such as Multi-Objective Invasive Weed Optimization, Multi-Objective Evolutionary Algorithm Based on Decomposition and Multi-Objective Grey Wolf Optimizer, which were rarely used in literature. Eventually, the most efficient algorithm was identified by comparing the considered algorithms. Springer US 2022-03-28 2022 /pmc/articles/PMC8958817/ /pubmed/35370360 http://dx.doi.org/10.1007/s10489-022-03334-5 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Raeisi, Diba
Jafarzadeh Ghoushchi, Saeid
A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions
title A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions
title_full A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions
title_fullStr A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions
title_full_unstemmed A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions
title_short A robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions
title_sort robust fuzzy multi-objective location-routing problem for hazardous waste under uncertain conditions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8958817/
https://www.ncbi.nlm.nih.gov/pubmed/35370360
http://dx.doi.org/10.1007/s10489-022-03334-5
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