A genetic algorithm for solving a maintenance model in a FMS

Maintenance float problems in a flexible manufacturing system structure are intractable. Therefore, there is a need for an enumerative sear ch method to solve such problems. This study presents a novel genetic algorithm to se arch for the optimal float and capacity of repair stations for FMS maintena nce float systems. The proposed algorithm is operated under a feasible set of failure rates to investigate how its performance dominates the enumerati ve search algorithm. Experimental results indicate that the genetic algorit hm is more promising than the enumerative search algorithm in searching for the best approximate solution and in minimizing the execution time.