Logistics Research Center, Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, China.
Shanghai Municipal Engineering Design Institute (Group) Co. LTD., Shanghai, China.
PLoS One. 2024 Nov 22;19(11):e0311536. doi: 10.1371/journal.pone.0311536. eCollection 2024.
The underground logistics system is a relatively new concept for container transportation, which is designed to reduce the congestion and pollution on the road caused by the sharply growing number of collections and distributions of containers in the port cities. This paper considers a system where some underground logistics vehicles (ULVs) are marshaled and used to transport containers between two port terminals through a deep underground tunnel. Automated guided vehicles (AGVs) are used for horizontal transportation of containers in the above-ground yard of the terminals, and yard cranes (YCs) are used to transfer the containers vertically through a shaft linking the above-ground yard and the deep underground tunnel. To guarantee the efficiency of this system, a joint scheduling problem of the YCs and the ULVs is proposed and formulated as an integer programming model to minimize the total waiting time of the YCs and ULVs. Taking marshaling and congestion of the ULVs into consideration, a Genetic Algorithm is developed to solve the problem. Numerical experimental results prove the efficiency of the proposed algorithm, and different marshaling strategies are compared. Our research provides a scientific foundation for developing underground logistics systems in large port cities.
地下物流系统是集装箱运输的一个相对较新的概念，旨在减少港口城市集装箱集疏运数量急剧增长对道路造成的拥堵和污染。本文考虑了一个系统，其中一些地下物流车辆（ULV）被编组并用于通过深层地下隧道在两个港口码头之间运输集装箱。自动导引车（AGV）用于码头地面堆场的集装箱水平运输，堆场起重机（YC）用于通过连接地面堆场和深层地下隧道的竖井垂直运输集装箱。为了保证该系统的效率，提出了一个联合调度 YC 和 ULV 的问题，并将其制定为一个整数规划模型，以最小化 YC 和 ULV 的总等待时间。考虑到 ULV 的编组和拥堵问题，开发了一种遗传算法来解决这个问题。数值实验结果证明了所提出算法的效率，并比较了不同的编组策略。我们的研究为在大型港口城市开发地下物流系统提供了科学依据。
