Applying the Extended Network Simplex Algorithm to Dynamic Automated Guided Vehicle Scheduling

Scheduling of vehicles in the container terminal is often studied as a static problem in the literature, where all information, including the number of jobs, their arrival time, etc., is known beforehand. The objective is generally minimizing the total travelling and/or waiting times of the vehicles. When the situation changes, for example new jobs arrive or a section of the terminal is blocked, new solutions are generated from scratch. In this paper, the problem of dynamically scheduling automated guided vehicles in the container terminals is formulated as a minimum cost flow problem. This problem is then solved by a novel algorithm, NSA+, which extended the standard Network Simplex Algorithm (NSA). Like NSA, NSA+ is a complete algorithm, which means it guarantees optimality of the solution if it finds one within the time available. Our software, DSAGV, employs NSA+ and can find the global optimal solutions for 3,000 jobs and 10 millions arcs in the graph model within 2 minutes on a 2.4 GHz Pentium PC. To complement NSA+, an incomplete algorithm Greedy Vehicle Search (GVS) is designed and implemented. To evaluate the relative strength and weakness of NSA+ and GVS, the two algorithms are compared for the dynamic automated vehicle scheduling problem. Both NSA+ and GVS are practical algorithms for dynamic automatic vehicle scheduling.