摘要
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 Al-gorithm,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.
To solve the Storage Space Allocation Problem （SSAP）, an optimization strategy for the stor- age 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.
出处
《上海海事大学学报》
北大核心
2012年第2期40-46,共7页
Journal of Shanghai Maritime University
基金
国家自然科学基金(71071093)
上海市自然科学基金(10ZR1413300)
上海市重点学科建设项目(J50604)
上海市科学技术委员会创新项目(09DZ2250400
9530708200
10190502500)
上海市教育委员会创新基金(11YZ136)
关键词
集装箱码头
岸桥
堆场空间资源配置
遗传算法
矩阵式编码
container terminal
quay crane
storage space allocation
genetic algorithm
matrix-based coding
