面向随机环境的集装箱码头泊位-岸桥分配方法

Study on berth and quay-crane allocation under stochastic environments in container terminal

针对船舶抵港时间和装卸时间的随机性,建立了面向随机环境的集装箱码头泊位-岸桥分配模型,其优化目标是最小化船舶的平均等待时间.考虑到模型求解的复杂度,本文设计了一种改进的遗传算法,并根据模型最优解的特点减少了搜索空间.试验算例验证了模型能够模拟码头泊位-岸桥分配问题的随机决策环境并能反映决策者对待风险的态度和偏好,其算法在允许的运算时间内能获得稳定的满意解.

Effective berth and quay-crane allocation improves service level of container terminal. Considering stochastic characteristic of containership arrival time and handling time, a berth ＆ quay-crane allocation model under stochastic environments is suggested, so as to minimize containership average waiting time in terminal. Because of its hardness, a genetic algorithm is developed with a reduced solution set on its property. Numerical experiments show that the model provides systemic simulation for the whole stochastic decision-making process and reflects decisionmaker risk attitude. And the results of GA are stable and acceptable in allowable CPU time.