American Journal of Modeling and Optimization
ISSN (Print): 2333-1143 ISSN (Online): 2333-1267 Website: http://www.sciepub.com/journal/ajmo Editor-in-chief: Dr Anil Kumar Gupta
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American Journal of Modeling and Optimization. 2016, 4(3), 67-73
DOI: 10.12691/ajmo-4-3-1
Open AccessArticle

Research on the Refined Oil Distribution Routing Problem Based on Ant-colony Algorithm

Zhenping Li1, , Zhiguo Wu1 and Lulu Jiang1

1School of Information, Beijing Wuzi University, Beijing, China

Pub. Date: August 23, 2016

Cite this paper:
Zhenping Li, Zhiguo Wu and Lulu Jiang. Research on the Refined Oil Distribution Routing Problem Based on Ant-colony Algorithm. American Journal of Modeling and Optimization. 2016; 4(3):67-73. doi: 10.12691/ajmo-4-3-1

Abstract

Refined oil distribution routing problem is defined as: Given the demand of each gas station and multiple types of oil tankers, how to distribute the refined oil from oil depot to meet the needs of each gas station so as to minimize the total cost. This paper mainly studies the distribution vechicles deployment and route planning of an oil company. With the consideration of capacity constraints of the tankers, demand, time window and unloading time of each gas station, a mathematical model is built which takes the minimum of system operating cost as the objective, and an improved ant-colony algorithm is designed to solve the model. Comparing the approximate optimal solution obtained by the improved ant-colony algorithm with the optimal solution obtained by Lingo software, the feasibility and effectiveness of the improved ant-colony algorithm for solving the refined oil distribution routing problem is verified.

Keywords:
distribution of refined oil routing problem time window ant-colony algorithm

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References:

[1]  HERER Y, LEVY R. The metered inventory routing problem, an integrative heuristic algorithm [J]. International Journal of Production Economics, 1997, 51(1): 69-81.
 
[2]  Birger Raa, El-Houssaine Aghezzaf. A practical solution approach for the cyclic inventory routing problem [J]. European Journal of Operational Research, 2007, 1922: 429-441.
 
[3]  BirgerRaa.New models and algorithms for the cyclic inventory routing problem [J]. 4OR, 2008, 61:97-100.
 
[4]  KunpengLi, Bin Chen, AppaIyer Sivakumar, Yong Wu. An inventory–routing problem with the objective of travel time minimization [J]. European Journal of Operational Research, 2014: 936-945.
 
[5]  Zhao Da, Li Jun, Ma Danxiang, Li Yanfeng. Optimization algorithm for solving stochastic demand inventory routing problem with hard time window constraints [J]. Operations research and management science, 2014, 23(1): 27-37.
 
[6]  Zhenping Li, Zhiguo Wu.Study on the inventory routing problem of refined oil distribution based on working time equilibrium [J].American Journal of Operations Research, 2016. 6(1): 17-24.
 
[7]  Wang Zhe. Research on VMI Inventory Routing Optimization Based on ant colony algorithm [D].Northeastern University, 2012.
 
[8]  Guo Meile. Research on Stochastic Demand Inventory Routing Problem Based on improved ant colony algorithm [D]. Northeastern University, 2011.
 
[9]  Han Jing. Research on lean logistics path optimization based on improved ant colony algorithm [D]. Wuyi University, 2008.