The HSABA for Emergency Location-Routing Problem
This article presents a Location-Routing Problem (LRP) model to assist decision makers in emergency logistics. The model attempts to consider the relationship between the location of warehouses and the delivery routes in order to maximize the rescue efficiency. The objective function of the minimiza...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/5391687 |
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doaj-7b69d4b92f8c4296ad8be7262d60e96f2020-11-25T00:42:01ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/53916875391687The HSABA for Emergency Location-Routing ProblemSiliang Luan0Qingfang Yang1Huxing Zhou2Zhongtai Jiang3Wei Wang4Zhuorui Wang5Ruijuan Chu6School of Transportation, Jilin University, Changchun, ChinaSchool of Transportation, Jilin University, Changchun, ChinaSchool of Transportation, Jilin University, Changchun, ChinaSchool of Transportation, Jilin University, Changchun, ChinaSchool of Transportation, Jilin University, Changchun, ChinaSchool of Transportation, Jilin University, Changchun, ChinaSchool of Transportation, Jilin University, Changchun, ChinaThis article presents a Location-Routing Problem (LRP) model to assist decision makers in emergency logistics. The model attempts to consider the relationship between the location of warehouses and the delivery routes in order to maximize the rescue efficiency. The objective function of the minimization of time and cost is established in the single-stage LRP model considering different scenarios. The hybrid self-adaptive bat algorithm (HSABA) is an improved nature-inspired algorithm for solving this LRP model, hard optimization problem. The HSABA with self-adaptation mechanism and hybridization mechanism effectively improves the defect of the original BA, that is, trapping into the local optima easily. An example is provided to prove the effectiveness of our model. The studied example shows that the single-stage LRP model can effectively select supply locations and plan rescue routes faced with different disasters and the HSABA outperforms the basic BA.http://dx.doi.org/10.1155/2019/5391687 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Siliang Luan Qingfang Yang Huxing Zhou Zhongtai Jiang Wei Wang Zhuorui Wang Ruijuan Chu |
spellingShingle |
Siliang Luan Qingfang Yang Huxing Zhou Zhongtai Jiang Wei Wang Zhuorui Wang Ruijuan Chu The HSABA for Emergency Location-Routing Problem Mathematical Problems in Engineering |
author_facet |
Siliang Luan Qingfang Yang Huxing Zhou Zhongtai Jiang Wei Wang Zhuorui Wang Ruijuan Chu |
author_sort |
Siliang Luan |
title |
The HSABA for Emergency Location-Routing Problem |
title_short |
The HSABA for Emergency Location-Routing Problem |
title_full |
The HSABA for Emergency Location-Routing Problem |
title_fullStr |
The HSABA for Emergency Location-Routing Problem |
title_full_unstemmed |
The HSABA for Emergency Location-Routing Problem |
title_sort |
hsaba for emergency location-routing problem |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2019-01-01 |
description |
This article presents a Location-Routing Problem (LRP) model to assist decision makers in emergency logistics. The model attempts to consider the relationship between the location of warehouses and the delivery routes in order to maximize the rescue efficiency. The objective function of the minimization of time and cost is established in the single-stage LRP model considering different scenarios. The hybrid self-adaptive bat algorithm (HSABA) is an improved nature-inspired algorithm for solving this LRP model, hard optimization problem. The HSABA with self-adaptation mechanism and hybridization mechanism effectively improves the defect of the original BA, that is, trapping into the local optima easily. An example is provided to prove the effectiveness of our model. The studied example shows that the single-stage LRP model can effectively select supply locations and plan rescue routes faced with different disasters and the HSABA outperforms the basic BA. |
url |
http://dx.doi.org/10.1155/2019/5391687 |
work_keys_str_mv |
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