基于计算物流的自动化集装箱码头AGV生产调度

Automated container terminal AGV production scheduling based oncomputational logistics

针对自动化集装箱码头自动导引车(AGV)在线实时生产调度约束动态复杂和难以可视化的问题,在计算物流框架下,利用AnyLogic平台创建自动化码头水平运输计算实验模型,并针对平台中已有的经典资源分配策略,面向AGV生产调度提出两方面的改进:将运筹规划商业求解器与计算实验平台结合来求解动态复杂组合优化问题;基于计算物流的思想方法,迁移和定制出五种面向问题探索的自定义AGV在线调度算法。由于商业求解器的局限性,模型和实验数据是基于自动化码头进口箱作业部分。实验表明,两种改进策略能够弥补商业求解器和计算实验平台的部分不足,尤其是自定义策略相较于经典资源分配策略能够面向特定装卸船需求更好地实现AGV生产调度,实现自动化码头水平运输的高效作业。

Addressing the issues of dynamic complicated constraints and the lack of visualization in automatic guided vehicle(AGV)scheduling at automated container terminals,this paper utilized the AnyLogic platform to construct a computational experiment model of an automated container terminal within the conceptual framework of computational logistics.It proposed two aspects of improvement for the AGV scheduling strategies within the model.Firstly,it employed the ILOG CPLEX to the AnyLogic system to solve dynamic complicated combinatorial optimization problem.Secondly,it devised five problem-oriented customized AGV scheduling strategies based on computational logistics.Due to the inhe-rent limitations of the CPLEX solver,the model and experimental data primarily focused on the import containers of the automated container terminal.The computational experiments demonstrate that the customized sche-duling strategies effectively complement the limitations of the CPLEX and the AnyLogic.In comparison to the original system policies,the customized strategies can better realize the production scheduling of AGVs for specific loading and unloading needs,while meeting efficient scheduling requirements.