Optimization model of network distribution planning on regional container ports

Zhao Xu; Yang Zan; Jin Zhi-hong; Ji Ming-jun

Volume 7 Issue 3

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Zhao Xu, Yang Zan, Jin Zhi-hong, Ji Ming-jun. Optimization model of network distribution planning on regional container ports[J]. Journal of Traffic and Transportation Engineering, 2007, 7(3): 44-49.

Citation:

Zhao Xu, Yang Zan, Jin Zhi-hong, Ji Ming-jun. Optimization model of network distribution planning on regional container ports[J]. Journal of Traffic and Transportation Engineering, 2007, 7(3): 44-49.

Zhao Xu, Yang Zan, Jin Zhi-hong, Ji Ming-jun. Optimization model of network distribution planning on regional container ports[J]. Journal of Traffic and Transportation Engineering, 2007, 7(3): 44-49.

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Optimization model of network distribution planning on regional container ports

School of Traffic Engineering and Logistics, Dalian Maritime University, Dalian 116026, Liaoning, China

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Author Bio:
Zhao Xu(1967-), female, associate professor, doctoral student of engineering, +86-411-84728385, zhao_xu@126.com

Yang Zan(1958-), male, EngD, professor, +86-411-84727232, yangzan@126.com
Received Date: 2006-11-10
Publish Date: 2007-06-25

Abstract

Abstract

In order to avoid the repetitive construction of container ports in transportation network, and realize the optimization distribution of ports, the general interaction and decision equilibrium between container port planner and user according to Stackelberg model were considered, and an optimization model of network distribution planning on regional container ports was established. In order to effectively reflect the individual properties of port users, the choice behaviors of micro-shippers were analyzed by using disaggregation theory according to their attributes. A genetic algorithm was designed to solve the model, its initial chromosome was generated by the matrix composed with the numbers of berths and corresponding voyage densities of different container ports, and the particularity of the model restrictions was considered. Example simulation result shows that the model is feasible, the approximative optimization port network planning of example computation accords with real analysis situation, the behaviors and influence factors of shippers can be reflected, and port optimization distribution can be realized.
- traffic planning,
- container port network,
- Stackelberg model,
- genetic algorithm,
- disaggregation theory

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References(16)

References

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