基于矩阵式遗传算法的集装箱码头堆场空间资源分配优化策略

摘要

To solve the Storage Space Allocation Problem (SSAP), an optimization strategy for the storage space allocation is proposed based on the Matrix Genetic Algorithm ( M-GA). The strategy aims at minimizing the transportation distance between the storage blocks and the vessel berths, and the factors such as quay crane and yard crane are taken into account. The storage space allocation model based on quay crane operating lines is built firstly; then the extended version of the SSAP is resolved by the M-GA; the influences of different genetic strategies on the performance of Genetic Algorithm (GA) are analyzed finally. The case of Shanghai Zhanghuabang Container Terminal verifies the superiority of the proposed method.%为解决堆场空间资源配置问题(Storage Space Allocation Problem,SSAP),以箱区到泊位运输距离最小为目标,综合考虑岸桥、场桥等因素,提出一种基于矩阵式遗传算法(Matrix Genetic Algorithm,M-GA)的集装箱码头堆场空间资源分配优化策略.该方法首先建立基于装卸作业面的堆场空间资源分配模型；然后运用M-GA求解扩展后的SSAP；最后分析不同遗传策略对遗传算法( Genetic Algorithm,GA)性能的影响,并以上海张华浜码头的案例验证该方法的优越性.