A genetic algorithm to solving the problem of flexible manufacturing system cyclic scheduling

We are interested in the determination of the command of Flexible Manufacturing Systems (FMS). We have chosen the Cyclic Behavior to reduce the complexity of the general,scheduling problem. The aim is to propose a new one based on genetic algorithms which can reach the optimal production speed while minimizing the Work in Process (W.I.P.). In fact we want to minimize the W.L.P. to satisfy economical constraints. The use of genetic algorithms is justified by the huge combinatorial complexity of such problems (NP hard in the general case). Indeed, this kind of algorithm is able to give a solution at any moment. Our approach was validated on a set of five FMS cyclic scheduling test problems.