Scheduling of AGV with Group Operation Area in Automated Terminal by Hybrid Genetic Algorithm

Scheduling is one of the very important tools for treating a complex combinatorial optimization problem (COP) model, where it can have a major impact on the productivity of a manufacturing process. Most models of scheduling are confirmed as NP-hard or NP-complete problems. The aim at scheduling is to find a schedule with the best performance through selecting resources for each operation, the sequence of each resource and the beginning time. Genetic algorithm (GA) is one of the most efficient methods among metaheuristics for solving the real-world manufacturing problems. In this paper, we survey the literature review on the optimization of Automate Guide Vehicle (AGV) transportation efficiency in the terminal, especially how to reduce the waiting time of AGV. From the point of AGV road blocking, the scheduling mode of group operation area is proposed. In order to minimize the maximum completion time of AGV, an AGV scheduling optimization model is established considering the interference constraints and AGV congestion in the actual operation of the terminal. Hybrid Genetic Algorithm with Fuzzy Logic Controller (HGA-FLC) is used to simulate the behavior of AGVs, and different scale examples are designed to solve the problem. Compared with GA, the experimental results show that this algorithm can effectively improve the efficiency of AGVs operation, reduce the waiting time and number of jams of AGV, which provide the basis of the actual operation of the terminal.