散货港装船设备分配与船舶交通组织协调优化
Optimization of Cargo Handling Machinery Allocation and Ship Traffic Organization for Bulk Cargo Ports
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摘要: 针对装船设备利用率与船舶进出港效率不匹配的问题,提出了一种应用于散货港口的装船设备分配与船舶交通组织协调优化模型,同时设计了一种基于启发式筛选规则的多目标遗传算法(Multi-Objective Genetic algorithm based on Heuristic Screening Rules,MOGA-HSR)。该算法融合了单向航道的船舶交通组织规则以及船货匹配规则,使用一种自适应交叉及变异概率函数,加快了求解的收敛速度。以黄骅港煤炭港区为例设计仿真试验,结果表明,MOGA-HSR求得的船舶进出港总时间和船舶总等待时间比带精英策略非支配排序的遗传算法(Genetic Algorithm for Non-Dominated Sorting with Elitist Strategy,NSGA-Ⅱ)求解结果分别缩短2.7 %和2.5 %,比先到先服务(First Come First Service,FCFS)求解结果分别缩短38 %和30.8 %,验证了模型和算法的有效性。Abstract: A model for bulk cargo ports to optimize cargo handling machinery allocation and ship traffic organization is introduced. A multi-objective genetic algorithm based on heuristic screen rules (MOGA-HSR) is designed. The algorithm integrates the traffic organization rules for one-way waterway and the cargo-ship matching rules. The self-adaptive crossover and mutation probability function is introduced to accelerate the convergence process. Simulations of Huanghua Coal Port are performed with MOGA-HSR and genetic algorithm for non-dominated sorting with elitist strategy (NSGA-Ⅱ), respectively. The simulation results show that the overall entering-leaving time and ship waiting time for the former are 2.7 % and 2.5 % shorter compared to those for the latter.And compared to the principle of first come first served (FCFS), they are shortened by 38 % and 30.8 % respectively, which demonstrated the effectiveness of the new method.