基于计算物流与计算智能的多码头泊位堆场联合调度

Joint Scheduling of Multiple Container Terminal Berth and Yard Based on Computational Logistics and Computational Intelligence

针对同一地区邻近集装箱码头往往物流功能相似、货源腹地重叠、无序竞争突出和资源利用率较低等特点,本文重点探讨了隶属于同一组织内且位置相邻多集装箱码头的泊位-堆场一体化计划调度(multiple container terminal tactical berth and yard incorporate integrative scheduling,MCT-TBY-IIS)问题.基于计算物流,利用多重多背包问题将MCT-TBY-IIS抽象和分解为考虑泊位水深约束和出口集装箱可转港作业的多码头动态连续泊位分配和多码头周期滚动堆场分配两个中度耦合子问题,进而在计算物流面向问题探索的思想下,提出了面向层次嵌套结构的二阶段改进帝国竞争算法(hierarchical nesting oriented two-stage improved imperialist competitive algorithm,HNOTSI-ICA)对MCT-TBY-IIS进行求解优化.最后,面向我国东南沿海的典型多码头联合作业实例,遴选出面向帝国兴替的双同化帝国竞争改进算法和面向0-1背包问题的二进制帝国竞争算法组合应用于HNO-TSI-ICA,其在求解MCT-TBY-IIS时效果较好,且堆场作业子系统目标成本的结构较稳定,其不受计划期内港口负荷和计划周期长度的影响,其中,出口箱区集装箱水平运输成本的贡献度在堆场作业子目标成本的比重最大,稳定在83%左右.通过对MCT-TBY-IIS的建模与优化,可以发现多码头联合作业模式有较好的潜力帮助同一组织内邻近的多码头降本增效和提高核心资源的利用率.

Considering the characteristics of the adjacent container terminals in the same region,such as similar logistics functions,overlapping cargo hinterlands,severe disorderly competition,and low resource utilization rates,this study focuses on the problem of multiple container terminal tactical berth and yard incorporate integrative scheduling(MCTTBY-IIS),where the terminals are managed by the same organization and located adjacent to each other.Based on computational logistics,the MCT-TBY-IIS problem is decomposed into two subproblems of moderate coupling:the multi-terminal dynamic and continuous berth allocation problem(MDC-BAP)and the multi-terminal periodic and rolling yard allocation problem(MPR-YAP).This decomposition is achieved by using the multiple knapsack problem,as well as considering berth depth constraints and export containers with transferable terminal options.Subsequently,the hierarchical nesting-oriented two-stage improved imperialist competitive algorithm(HNO-TSI-ICA)is customized to optimize MCT-TBY-IIS under the guidance of problem-oriented exploration.Lastly,with typical examples of multiterminal joint operations in the southeast coastal region in China,a combination of two algorithms is selected and applied to HNO-TSI-ICA for solving the MCT-TBY-IIS problem:the prosperity and destruction-oriented improved imperialist competitive algorithm with double assimilation,and the binary imperialist competitive algorithm for the 0-1 knapsack problem.Moreover,the structure of the target cost of the storage yard operation subsystem is stable and not affected by the port load or the length of the planning period.Notably,the horizontal transportation cost of containers in the export container area makes the largest contribution to the sub-target cost of storage yard operations,maintaining a stable proportion of 83%.Through the modeling and optimization of MCT-TBY-IIS,it is found that the multi-terminal cooperative operation mode has great potential to help the neighboring multiple terminals in the same organization reduce costs,increase efficiency,and improve the utilization rate of core resources.