Research on the Optimization of Transportation Routing Problem of Warehouse Material Based on Self-Adaptive Ant Colony Algorithm

Guang Rong Bian; Hong Sheng Li; Ge Lin Dai

doi:10.4028/www.scientific.net/AMM.236-237.1122

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 236-237Research on the Optimization of Transportation...

Research on the Optimization of Transportation Routing Problem of Warehouse Material Based on Self-Adaptive Ant Colony Algorithm

Abstract:

Ant colony algorithm is an intelligent optimization algorithm derives heuristically from simulating ants to seek food, the paper firstly creates the VRP model of warehouse material transportation,self-adaptive ant colony algorithm is used for solving the model. This paper gives some measures to improve the Ant colony algorithm in the procedure to seek the solution.At last, the experimental results based on MATLAB show that this algorithm is extremely effective to solve the optimal solutions of VRP. Its application in VRP has achieved good results.

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Periodical:

Applied Mechanics and Materials (Volumes 236-237)

Pages:

1122-1127

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.236-237.1122

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Online since:

November 2012

Authors:

Guang Rong Bian, Hong Sheng Li, Ge Lin Dai

Keywords:

Self-Adaptive ACO, Transportation Routing Optimization, Warehouse Material

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References

[1] H. Ayed, D. Khadraoui, Z. Habbas, P. BouvryandJ-F Merche, Transfer graph approach for MultimodalTransport Problems , International ConferenceonModelling, Computation and Optimization in Information Systems, MCO'2008, MetzLuxembourg, 2008 , pp.538-547.

DOI: 10.1007/978-3-540-87477-5_57

Google Scholar

[2] H. Ayed, D. Khadraoui, Z. Habbas, Deployment of a new optimization technique on transfer-graph, validation in Multimodal Transport Problem, In international workshop of Logistic and Transport LT 2009, Sousse-Tunisie(2009).

Google Scholar

[3] MEI Dong, SHI Xiaoyan ; ZHAO Fanggeng, An improved ACO algorithm for vehicle scheduling problem in military material distribution, 2009 IEEE International Conference on Grey Systems and Intelligent Services(2009).

DOI: 10.1109/gsis.2009.5408169

Google Scholar

[4] Y. J. Zhong, M. H. Cole, A vehicle routing problem with backhauls and time windows: a guided local search solution, Transportation Research Part E, Vol. 41, Jan. 2005, pp.131-144.

DOI: 10.1016/j.tre.2003.12.003

Google Scholar

[5] A. Colorni, M. Dorigo, V. Maniezzo, M. Trubian, Ant system for job-shop scheduling problem, Belgian Journal of Operation Research, Statistics and Computer Science, Vol. 34 , 1994 , pp.39-53.

Google Scholar

[6] T. Stützle, H. Hoos, MAX-MIN Ant System, Future Generation Computer Systems, Vol. 16, Jun. 2000, p.889–914.

DOI: 10.1016/s0167-739x(00)00043-1

Google Scholar