An intelligent integrated scheduling model for Flexible Manufacturing System

This paper deals with the simultaneous scheduling of incoming jobs, machines, and vehicle dispatching in a flexible manufacturing system (FMS) having a single device, an automated guided vehicle (AGV). The objective is to find an optimal sequence of incoming parts, which will reduce the waiting times due to blocking and starving of resources and deadheading times, resulting in overall minimization of makespan. In this work a genetic algorithm based iterative procedure which accommodates the combinatorial nature of the problem is proposed to approximately solve the integrated scheduling problem. The procedure is evaluated through different benchmark problems and the outcome of the study is encouraging and paves the way for further research in this area.