摘要
为获得使集装箱码头综合利益最大的泊位调度方案,建立了以船舶平均在港时间、码头生产成本和安全质量为目标的多目标优化模型;采用改进的强度Pareto进化算法(SPEA2)进行求解,基本操作中,可行解用三层染色体结构表示,改进的两点交叉算子和基于领域搜索的变异算子可避免出现不可行解,同时给出了靠泊顺序推迟最小的Pareto最优解选择策略。某集装箱码头的试验算例表明,文中提出的优化方法不仅能获得较优的满意解,同时收敛速度较快,可作为集装箱码头泊位调度的有效手段。
To gain a berth allocation plan with the maximum benefit of the container terminal company,a multi-objective optimization model was established with the average transship time of ships,the production cost and the safe mass considered.The improved Strength Pareto Evolutionary Algorithm（SPEA2） was adopted.Feasible solutions were expressed by chromosomes with three-level structure.And an improved cross operator and a mutation with neighborhood search were used to avoid infeasible solutions.Moreover,a selection strategy was given to minimize the deviation between the service order and the arrival sequence of the ships.Experiments based on some container terminal in China were given to verify the model and method.The results show that the proposed approach can obtain a better satisfaction solution quickly,and can be used in berth allocation in container terminals.
出处
《工业工程与管理》
北大核心
2010年第3期100-104,共5页
Industrial Engineering and Management
关键词
集装箱码头
泊位调度
多目标优化
SPEA2
container terminal
berth allocation
multi-objective optimization
SPEA2
