The most complex problem in FMS is scheduling task, due to this complexity it has created interest among many researchers. Even though FMS scheduling problem was considered earlier, material handling systems like (AGVs) scheduling was not done effectively. As transportation times cannot be neglected in an FMS, a carefully managed and designed material handling system is important in achieving the required integration in flexible manufacturing environment. Hence there is a need for scheduling both the machines and material handling system simultaneously for the successful implementation of an FMS, which makes the scheduling of FMS more complex. Metaheuristic Algorithms are mostly received by the researchers, because of their capability to tackle more complex problems. Hybridization of the metaheuristics may further improve their performance. In the present work a new hybrid metaheuristic Teaching Learning based optimization(HTLBO) is proposed to solve simultaneous scheduling problems.

Flexible Manufacturing System (FMS) is a compound system containing essentials like workplaces, computerized storing and recovery systems, and material control devices such as automatons and automated guided vehicles (AGVs). In this paper, an attempt is made to study concurrently the machine and vehicle planning features in an FMS for minimization of the makespan. Planning is concerned with the distribution of partial resources to tasks over time and it is a resolution making procedure. It associates the processes, time, cost and overall purposes of the company. In this work, Nawaz-Enscore-Ham (NEH) heuristic algorithm is implemented to solve the scheduling problems in FMS. Eighty two problems and their existing solutions with different approaches are examined. The preliminary results indicate that the NEH heuristic algorithm provides better solutions with less computational time.

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