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Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness
With the development of the express delivery industry, how to increase the recycling rate of waste cartons has become a problem that needs to be solved. Recycling enterprises began to provide the new recycling mode, door-to-door recycling services, to residents with waste cartons. In this article, w...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495949/ https://www.ncbi.nlm.nih.gov/pubmed/37705651 http://dx.doi.org/10.7717/peerj-cs.1519 |
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author | Xi, Yulong Tao, Fengming Brooks, Schanelle |
author_facet | Xi, Yulong Tao, Fengming Brooks, Schanelle |
author_sort | Xi, Yulong |
collection | PubMed |
description | With the development of the express delivery industry, how to increase the recycling rate of waste cartons has become a problem that needs to be solved. Recycling enterprises began to provide the new recycling mode, door-to-door recycling services, to residents with waste cartons. In this article, we constructed a site selection model for a carton recycling site with the aim of maximizing total profits. Considering the residents’ recycling willingness and the government subsidy earned through the contribution to carbon emission reduction, this model achieves the task of site selection and unit price fixation for carton recycling. We used the particle swarm optimization (PSO) algorithm to solve the model and compared it with the genetic algorithm (GA) for validity testing. PSO algorithm was also used to carry out sensitivity analysis in this model. The proposed model and the results of the sensitivity analysis can be used for decision-making in recycling enterprises as well as for further research on waste recycling and reverse logistics. |
format | Online Article Text |
id | pubmed-10495949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104959492023-09-13 Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness Xi, Yulong Tao, Fengming Brooks, Schanelle PeerJ Comput Sci Algorithms and Analysis of Algorithms With the development of the express delivery industry, how to increase the recycling rate of waste cartons has become a problem that needs to be solved. Recycling enterprises began to provide the new recycling mode, door-to-door recycling services, to residents with waste cartons. In this article, we constructed a site selection model for a carton recycling site with the aim of maximizing total profits. Considering the residents’ recycling willingness and the government subsidy earned through the contribution to carbon emission reduction, this model achieves the task of site selection and unit price fixation for carton recycling. We used the particle swarm optimization (PSO) algorithm to solve the model and compared it with the genetic algorithm (GA) for validity testing. PSO algorithm was also used to carry out sensitivity analysis in this model. The proposed model and the results of the sensitivity analysis can be used for decision-making in recycling enterprises as well as for further research on waste recycling and reverse logistics. PeerJ Inc. 2023-08-24 /pmc/articles/PMC10495949/ /pubmed/37705651 http://dx.doi.org/10.7717/peerj-cs.1519 Text en © 2023 Xi et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Algorithms and Analysis of Algorithms Xi, Yulong Tao, Fengming Brooks, Schanelle Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness |
title | Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness |
title_full | Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness |
title_fullStr | Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness |
title_full_unstemmed | Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness |
title_short | Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness |
title_sort | optimization of carton recycling site selection using particle swarm optimization algorithm considering residents’ recycling willingness |
topic | Algorithms and Analysis of Algorithms |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495949/ https://www.ncbi.nlm.nih.gov/pubmed/37705651 http://dx.doi.org/10.7717/peerj-cs.1519 |
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