英语翻译第一部分,在“泊位资源配置”模型构建中以船舶在泊时间最短为目标,建立了动态泊位资源分配的整数规划模型,运用码头实际数据通过eM-plant仿真系统加以验证得出了泊位动态配置
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英语翻译第一部分,在“泊位资源配置”模型构建中以船舶在泊时间最短为目标,建立了动态泊位资源分配的整数规划模型,运用码头实际数据通过eM-plant仿真系统加以验证得出了泊位动态配置
英语翻译
第一部分,在“泊位资源配置”模型构建中以船舶在泊时间最短为目标,建立了动态泊位资源分配的整数规划模型,运用码头实际数据通过eM-plant仿真系统加以验证得出了泊位动态配置模型是可行和有效的结论.
第二部分,在“岸边作业”模型构建中,以船舶作业时间最低为目标,结合岸桥装卸作业线分配、作业顺序安排以及岸桥调配方式建立了整数规划模型,并通过实际数据编制案例验证得出：船舶到港密度与岸桥分配方式的关系,从而有效的解决岸桥在泊位之间如何调配的问题.
第三部分,在“水平机械配置”模型构建中,通过建立一个网络最小流优化模型来解决集卡调度方案的优化问题,采用码头实际作业数据设计了一个实例,并运用建立的集装箱码头水平运输模型进行求解,得到最优的集卡配置方案.
英语翻译第一部分,在“泊位资源配置”模型构建中以船舶在泊时间最短为目标,建立了动态泊位资源分配的整数规划模型,运用码头实际数据通过eM-plant仿真系统加以验证得出了泊位动态配置
The first part, in the "berth allocation of resources" model is built to ship on berth time shortest as the goal, to establish the dynamic berth allocation of resources of the integer programming model, using wharf actual data through the eM - plant simulation system verified it is concluded that the berth dynamic allocation model is feasible and effective conclusion. The second part, in "the shore operations" model in the construction, in order to ship operating time minimum as the goal, combined with shore bridge handling operating line distribution, operation sequence and shore bridge deployment mode established the integer programming model, and through the actual data compilation case validation draw: the arrival density and the shore bridge distribution mode relations, so as to effectively solve the land bridge between the berth how to allocate problem. The third part, in the "horizontal mechanical configuration" model is built, by establishing a network minimum flow optimization model to solve set card scheduling scheme optimization problem, the terminal practical work data design a examples, and use a container terminal level transport model is solved, got the best collection card configuration scheme.