摘要
在集装箱港口的运作中,泊位调度系统是制约集装箱港口降低船舶在港时间和运营成本的主要瓶颈之一.泊位调度问题是NP难问题,本文分别应用遗传算法GA和混合优化策略GATS对泊位调度问题的非线性规划模型进行了求解.与遗传算法相比,混合优化策略GATS增加了种群多样性,加速了进化过程,避免陷入局部极小解.
In the operations of the container ports, the berth scheduling problem is one of the main bottlenecks that restrict the container port to reduce the turnaround time of the ships and the operation costs. The berth scheduling problem is an NPhard problem. This paper solves an nonlinear model of the berth scheduling problem by the genetic algorithm GA and the hy- brid optimization strategy GATS respectively. Compared with the genetic algorithm, the hybrid optimization strategy GATS increased the diversity of the individuals, and the evolution process as well as sinking into the local minimal solution.
出处
《天津理工大学学报》
2006年第4期58-61,共4页
Journal of Tianjin University of Technology
基金
天津市高校科技发展基金项目(20041706)
关键词
泊位调度
混合优化策略GATS
遗传算法
禁忌搜索算法
berth scheduling
hybrid optimization strategy GATS
genetic algorithm
taboo search algorith