Scheduling of AGV in Flexible Manufacturing System using Metaheuristics Techniques

AGV-based automated guided vehicles (AGVs) are used in the Flexible Manufacturing System (FMS), which was developed and put into use to increase production flexibility and efficiency. The scheduling of resources, such as the frequently changing parts, tools, and AGV routings, after the introduction of FMS, in practice, becomes a challenging problem. Traditional methods for doing this include a variety of mathematical programming techniques. Random search methods have been tested for scheduling in recent years. Single goal optimization has been the focus of the majority of studies. Conflicting objectives in multi-objective scheduling problems are more difficult and combinatorial in nature, and they rarely have a single solution. This study looks at AGV multi- objective work scheduling in a flexible production environment. The goal of this study was to identify the most ideal schedule for two AGVs based on a balanced workload and the shortest trip distance for maximum utilization. AGV's, Benchmark problem, Combinatorial optimization problem, Differential Evolution, Flexible manufacturing system, Job shop scheduling