Network model and effective evolutionary approach for AGV dispatching in manufacturing system
Automated guided vehicles (AGVs), are the state-of-the-art, and are often used to facilitate automatic storage and retrieval systems (AS/RS). In this paper, we focus on the dispatching of AGVs in a flexible manufacturing system (FMS). A FMS environment requires a flexible and adaptable material handling system. We model an AGV system by using network structure. This network model of an AGV dispatching has simplexes decision variables with considering most AGV problem's constraints, for example capacity of AGVs, precedence constraints among the processes, deadlock control. Furthermore, these problems can be solved by using a lot of heuristic algorithms as network optimization problems. We are also proposed an effective evolutionary approach for solving a kind of AGV's problems in which minimizing time required to complete all jobs (i.e. makespan) and minimizing the number of AGVs, simultaneously. For applying an evolutionary approach for this multicriteria case of AGV problem, priority-based encoding method and Interactive Adaptive-weight GA (i-awGA) were proposed. Numerical analyses for case study show the effectiveness of proposed approach.
automated guided vehicles (agv) flexible manufacturing system (fms) network flows priority-based genetic algorithm (priga)