考虑航速优化的多港口泊位协同调度

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.

Multi-port Berth Co-scheduling with Speed Optimization

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.