Study on Vehicle Logistics Routing Path Problem with Time Windows Based on Particle Swarm Optimization

Lian Zhou Gao

doi:10.4028/www.scientific.net/AMM.687-691.5161

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 687-691Study on Vehicle Logistics Routing Path Problem...

Study on Vehicle Logistics Routing Path Problem with Time Windows Based on Particle Swarm Optimization

Abstract:

As the development of world economy, how to realize the reasonable vehicle logistics routing path problem with time window constrain is the key issue in promoting the prosperity and development of modern logistics industry. Through the research of vehicle logistics routing path 's demand, particle swarm optimization with a novel particle presentation is designed to solve the problem which is improved, effective and adept to the normal vehicle logistics routing. The simulation results of example indicate that the algorithm has more search speed and stronger optimization ability.

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Periodical:

Applied Mechanics and Materials (Volumes 687-691)

Pages:

5161-5164

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.687-691.5161

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Online since:

November 2014

Authors:

Lian Zhou Gao*

Keywords:

Effective, Logistics Routing Path, Particle Swarm Optimization (PSO)

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* - Corresponding Author

References

[1] Liping Zhang. Logistics path problem of the improved genetic algorithm [J]. Journal of systems engineering theory and practice, 2007, 8 (8) : 79-84.

Google Scholar

[2] Jing-ling zhang. More dynamic demand logistics path problem modeling and optimization models [J]. Journal of computer integrated manufacturing system, 2010 (3) : 543-550.

Google Scholar

[3] Kennedy J. Eberhart R. Particle Swarm Optimization [A]．in: Proceedings of IEEE International Conference on Neural Networks[C]．1995．1942—1948.

Google Scholar

[4] Maurice Clerc, James Kennedy. The particle swarm-explosion, stability, and convergence in a multidimensional complex space [J]. IEEE Transaction on Evolutionary Computation, 2002, 6(1): 58-73.

DOI: 10.1109/4235.985692

Google Scholar

[5] Ayed Salmen, Imtiaz Ahmad, Sabah Al-Madani. Particle swarm optimization for task assignment problem [J]. Microprocessors and Microsystems, 2002, 26: 363-371.

DOI: 10.1016/s0141-9331(02)00053-4

Google Scholar