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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
引用本文:顾天意,梁承姬.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[J].上海海事大学学报,2012,33(2):40-46.
作者姓名:顾天意  梁承姬
作者单位:上海海事大学科学研究院,上海,201306
基金项目: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)
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 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.

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
收稿时间:2011/10/22 0:00:00
修稿时间:2/15/2012 2:12:05 PM

An optimization strategy for storage space allocation in container terminal based on matrix genetic algorithm
GU Tianyi , LIANG Chengji.An optimization strategy for storage space allocation in container terminal based on matrix genetic algorithm[J].Journal of Shanghai Maritime University,2012,33(2):40-46.
Authors:GU Tianyi  LIANG Chengji
Institution:Shanghai Maritime University
Abstract: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.
Keywords:container terminal  quay crane  storage space allocation  genetic algorithm  matrix based coding
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