Optimizing Route for Hazardous Materials Logistics Based on Hybrid Ant Colony Algorithm

Optimizing Route for Hazardous Materials Logistics (ORHML) belongs to a class of problems referred to as NP-Hard, and a strict constraint of it makes it harder to solve. In order to dealing with ORHML, an improved hybrid ant colony algorithm (HACA) was devised. To achieve the purpose of balancing ri...

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Main Authors: Haixing Wang, Guiping Xiao, Zhen Wei
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2013/752830
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author Haixing Wang
Guiping Xiao
Zhen Wei
author_facet Haixing Wang
Guiping Xiao
Zhen Wei
author_sort Haixing Wang
collection DOAJ
description Optimizing Route for Hazardous Materials Logistics (ORHML) belongs to a class of problems referred to as NP-Hard, and a strict constraint of it makes it harder to solve. In order to dealing with ORHML, an improved hybrid ant colony algorithm (HACA) was devised. To achieve the purpose of balancing risk and cost for route based on the principle of ACA that used to solve TSP, the improved HACA was designed. Considering the capacity of road network and the maximum expected risk limits, a route optimization model to minimize the total cost is established based on network flow theory. Improvement on route construction rule and pheromone updating rule was adopted on the basis of the former algorithm. An example was analyzed to demonstrate the correctness of the application. It is proved that improved HACA is efficient and feasible in solving ORHML.
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publishDate 2013-01-01
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record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-c6cf8221e9de49bba625a3b0214ac76e2025-08-20T02:19:41ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2013-01-01201310.1155/2013/752830752830Optimizing Route for Hazardous Materials Logistics Based on Hybrid Ant Colony AlgorithmHaixing Wang0Guiping Xiao1Zhen Wei2Beijing Jiaotong University, Beijing 100044, ChinaBeijing Jiaotong University, Beijing 100044, ChinaBeijing Jiaotong University, Beijing 100044, ChinaOptimizing Route for Hazardous Materials Logistics (ORHML) belongs to a class of problems referred to as NP-Hard, and a strict constraint of it makes it harder to solve. In order to dealing with ORHML, an improved hybrid ant colony algorithm (HACA) was devised. To achieve the purpose of balancing risk and cost for route based on the principle of ACA that used to solve TSP, the improved HACA was designed. Considering the capacity of road network and the maximum expected risk limits, a route optimization model to minimize the total cost is established based on network flow theory. Improvement on route construction rule and pheromone updating rule was adopted on the basis of the former algorithm. An example was analyzed to demonstrate the correctness of the application. It is proved that improved HACA is efficient and feasible in solving ORHML.http://dx.doi.org/10.1155/2013/752830
spellingShingle Haixing Wang
Guiping Xiao
Zhen Wei
Optimizing Route for Hazardous Materials Logistics Based on Hybrid Ant Colony Algorithm
Discrete Dynamics in Nature and Society
title Optimizing Route for Hazardous Materials Logistics Based on Hybrid Ant Colony Algorithm
title_full Optimizing Route for Hazardous Materials Logistics Based on Hybrid Ant Colony Algorithm
title_fullStr Optimizing Route for Hazardous Materials Logistics Based on Hybrid Ant Colony Algorithm
title_full_unstemmed Optimizing Route for Hazardous Materials Logistics Based on Hybrid Ant Colony Algorithm
title_short Optimizing Route for Hazardous Materials Logistics Based on Hybrid Ant Colony Algorithm
title_sort optimizing route for hazardous materials logistics based on hybrid ant colony algorithm
url http://dx.doi.org/10.1155/2013/752830
work_keys_str_mv AT haixingwang optimizingrouteforhazardousmaterialslogisticsbasedonhybridantcolonyalgorithm
AT guipingxiao optimizingrouteforhazardousmaterialslogisticsbasedonhybridantcolonyalgorithm
AT zhenwei optimizingrouteforhazardousmaterialslogisticsbasedonhybridantcolonyalgorithm