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Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm
Emergency management is conceptualized as a complex, multi-objective optimization problem related to facility location. However, little research has been performed on the horizontal transportation of emergency logistics centres. This study makes contributions to the multi-objective locating abrupt d...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10454948/ https://www.ncbi.nlm.nih.gov/pubmed/33970045 http://dx.doi.org/10.1177/00368504211016205 |
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author | Sun, Qiang Liu, Shupei |
author_facet | Sun, Qiang Liu, Shupei |
author_sort | Sun, Qiang |
collection | PubMed |
description | Emergency management is conceptualized as a complex, multi-objective optimization problem related to facility location. However, little research has been performed on the horizontal transportation of emergency logistics centres. This study makes contributions to the multi-objective locating abrupt disaster emergency logistics centres model with the smallest total cost and the largest customer satisfaction. The IABC algorithm is proposed in this paper to solve the multi-objective emergency logistics centres locating problem. IABC algorithm can effectively calculate the optimal location of abrupt disaster emergency logistics centres and the demand for relief materials, and it can solve the rescue time satisfaction for different rescue sites. (1) IABC has better global search capabilities to avoid premature convergence and provide a faster convergence speed, and it has optimal solution accuracy, solution diversity and robustness. (2) From the three optimal objective function values obtained, the optimal objective function values obtained by IABC algorithm are obviously better than ABC and GABC algorithms. (3) From the convergence curves of three objective functions the global search ability and the stability of IABC algorithm are better than those of ABC and GABC algorithm. The improved ABC algorithm has proven to be effective and feasible. However, emergency relief logistics systems are very complex and involve many factors, the proposed model needs to be refined further in the future. |
format | Online Article Text |
id | pubmed-10454948 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-104549482023-08-26 Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm Sun, Qiang Liu, Shupei Sci Prog Article Emergency management is conceptualized as a complex, multi-objective optimization problem related to facility location. However, little research has been performed on the horizontal transportation of emergency logistics centres. This study makes contributions to the multi-objective locating abrupt disaster emergency logistics centres model with the smallest total cost and the largest customer satisfaction. The IABC algorithm is proposed in this paper to solve the multi-objective emergency logistics centres locating problem. IABC algorithm can effectively calculate the optimal location of abrupt disaster emergency logistics centres and the demand for relief materials, and it can solve the rescue time satisfaction for different rescue sites. (1) IABC has better global search capabilities to avoid premature convergence and provide a faster convergence speed, and it has optimal solution accuracy, solution diversity and robustness. (2) From the three optimal objective function values obtained, the optimal objective function values obtained by IABC algorithm are obviously better than ABC and GABC algorithms. (3) From the convergence curves of three objective functions the global search ability and the stability of IABC algorithm are better than those of ABC and GABC algorithm. The improved ABC algorithm has proven to be effective and feasible. However, emergency relief logistics systems are very complex and involve many factors, the proposed model needs to be refined further in the future. SAGE Publications 2021-05-10 /pmc/articles/PMC10454948/ /pubmed/33970045 http://dx.doi.org/10.1177/00368504211016205 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Article Sun, Qiang Liu, Shupei Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm |
title | Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm |
title_full | Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm |
title_fullStr | Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm |
title_full_unstemmed | Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm |
title_short | Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm |
title_sort | locating abrupt disaster emergency logistics centres using improved artificial bee colony (iabc) algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10454948/ https://www.ncbi.nlm.nih.gov/pubmed/33970045 http://dx.doi.org/10.1177/00368504211016205 |
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