计算机应用 ›› 2012, Vol. 32 ›› Issue (02): 448-451.DOI: 10.3724/SP.J.1087.2012.00448

• 人工智能 • 上一篇    下一篇

集装箱港口集群下多港口多泊位联合调度方法

毕娅1,2,李文锋2   

  1. 1. 湖北经济学院 物流与工程管理学院,武汉 430205
    2. 武汉理工大学 物流工程学院,武汉 430063
  • 收稿日期:2011-07-29 修回日期:2011-09-22 发布日期:2012-02-23 出版日期:2012-02-01
  • 通讯作者: 毕娅
  • 作者简介:毕娅(1978-),女,湖北武汉人,讲师,博士研究生,主要研究方向:物流仿真与优化软件;
    李文锋(1966-),男,湖南岳阳人,教授,博士生导师,主要研究方向:虚拟制造、物流仿真、机器人设备与装备。
  • 基金资助:
    重庆市重大科技专项(CSTC,2009AA2028);中国博士后科学基金资助项目(20090451087);湖北省物流发展研究中心资助项目(2011B04)

Multi-port and multi-berth integrated scheduling based on container port cluster

BI Ya1,2,LI Wen-feng2   

  1. 1. School of Logistics and Engineering Management, Hubei University of Economics, Wuhan Hubei 430205, China
    2. School of Logistics Engineering, Wuhan University of Technology, Wuhan Hubei 430063, China
  • Received:2011-07-29 Revised:2011-09-22 Online:2012-02-23 Published:2012-02-01
  • Contact: BI Ya

摘要: 目前对港口和泊位的调度研究尚停留在单港口多泊位,而在集装箱港口集群条件下对多港口多泊位实行船舶的联合调度可以充分实现港口资源的优化配置。为了充分利用港口资源,实现船舶在港时间最短,且服从船公司运输成本最低的目的,建立了集装箱港口集群下多港口多泊位联合调度的多目标非线性决策模型,并按照模型决策空间所具有的特殊条件,设计了改进的遗传启发式算法,结果表明船舶靠泊成本大幅降低,港口利用率大幅提高。通过大量真实和随机算例验证了算法的有效性和稳定性,证明了模型和算法实用有效。

关键词: 集装箱港口集群, 联合调度, 多目标决策模型, 启发式算法

Abstract: The current schedule of ports and berths still remains in the single-port multi-berth, while multi-port and multi-berth integrated scheduling based on the container port cluster can achieve the optimal allocation of ports resources, reduce the time in port and improve the resource utilization rate, and at the same time, the optimal transportation cost of the ship company has been taken into account. Therefore, the multi-objective non-linear programming model for multi-port and multi-berth integrated scheduling system was constructed with certain assumptions as premises. Then, a heuristic algorithm for the model was designed according to the specific structure of the model's decision-making space. Finally, the numerical calculation was performed in order to verify the effectiveness and stability of the algorithm. It shows that the decision model is practical and the algorithm is valid.

Key words: container port cluster, integrated scheduling, multi-objective decision model, heuristic algorithm

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