Journal of Transportation Systems Engineering and Information Technology ›› 2019, Vol. 19 ›› Issue (6): 215-222.

• Systems Engineering Theory and Methods • Previous Articles     Next Articles

Multi-port Berth Co-scheduling with Speed Optimization

YANG Jie1, LI Ting2, BAI Peng-rui1   

  1. 1. School of Management Science & Engineering, Shanxi University of Finance and Economics, Taiyuan 030006, China; 2. School of Transportation Engineering, Shandong Jianzhu University, Jinan 250101, China
  • Received:2019-08-20 Revised:2019-10-18 Online:2019-12-25 Published:2019-12-25

考虑航速优化的多港口泊位协同调度

杨劼*1,李婷2,白鹏锐1   

  1. 1. 山西财经大学管理科学与工程学院,太原 030006;2. 山东建筑大学交通工程学院济南 250101
  • 作者简介:杨劼(1987-),女,山西临汾人,讲师,博士.
  • 基金资助:

    山西省高等学校科技创新项目/Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi Province, China(2019L0494);山西省哲学社会科学规划课题/Program for the Philosophy and Social Sciences Research in Shanxi Province, China(2019B123);山西财经大学青年科研基金/Foundation for Youth Teachers in Shanxi University of Finance and Economics(QN-2018018).

Abstract:

The container transport has been playing an important role in the global trading system, and it also faces many challenges and opportunities brought about by globalization. In this paper, the multi-port BAP which is extended from the classical single-port BAP is solved. We establish a multi-port berth co-scheduling model with the aim of minimizing the total cost. Considering the impact of vessel' s sailing speed on its arrival time at a port and fuel consumption, the speeds of vessels are formulated as decision variables. We introduce an improved genetic algorithm to solve the mathematical model. Experiments with artificial test instances are performed. The results indicate that speed optimization can help reducing the total cost of the operation, and obtaining far better economic and environmental benefits.

Key words: waterway transportation, berth co-scheduling, mixed integer programming, speed optimization, container terminal

摘要:

集装箱运输在全球贸易体系中发挥着重要作用,同时也面临着全球化带来的各种挑战和机遇. 将经典的单港泊位调度问题(BAP)拓展到航运网络中的多个港口进行优化研究. 考虑航速直接影响船舶到港时间和能耗,将船舶航速作为决策变量,以所有船舶总的在港成本最小为目标,建立泊位协同调度模型. 依据模型特点,设计改进的遗传算法对模型求解. 通过数值实验验证模型的性能,结果表明:对不同规模的调度问题进行航速优化,有利于降低船舶总的在港成本;依据燃油价格的变化,适时采用不同的航速策略,能够获得更好的经济和环境效益.

关键词: 水路运输, 泊位协同调度, 混合整数规划, 航速优化, 集装箱港口

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