关键词: 港口, 调度, 多目标优化, 粒子群算法, 最优解

Abstract: Aiming at the demand of dredging dispatching after a large number of ships waiting in the port,a multi-objective optimization model of dredging dispatching based on flexible berthing was constructed with the shortest average waiting time and the lowest additional operation cost.The adaptive particle swarm algorithm was used to solve the problem with the neighborhood search rule embedded in the calculation process.Based on the obtained Pareto non-inferior solution set,the optimal solution accepted by both the shipping companies and the port parties was obtained by mining the feature of Pareto front distribution,taking into account the unbiased concept of the interests of both shipping companies and port parties.The rationality of the model and the solving method was validated by actual case of Dalian port container terminal.Compared with the both conventional particle swarm algorithm and NSGA-II algorithm,the improved algorithm could obtain the optimal solution in a shorter time,and had better stability.

Key words: port, scheduling, multi-objective optimization, particle swarm algorithm, optimal solution