Simultaneous Scheduling of Machines and AGVs Using Crow Search Algorithm: A New Nature-Inspired Meta-Heuristic

This paper addresses the problem of simultaneous scheduling of machines and two identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS). It is a NP–hard problem which is very complex. For solving this problem, a new nature inspired meta-heuristic Crow Search Algorithm (CSA) is proposed. The problem consists of two interrelated problems, scheduling of machines and scheduling of AGVs. A simultaneous scheduling of these, in order to minimize the makespan will result in an FMS being able to complete all the jobs assigned to it at earliest time possible, thus saving resources. Improvement in performance of FMS can be expected by efficient utilization of its resources, by proper integration and synchronization of their scheduling. The proposed heuristic is tested on problems generated by various researchers and the results are compared with the results of existing methods. The results show that the proposed heuristic outperforms the existing methods.