Model optimization of flexible manufacturing systems based on hybrid genetic algorithms

The increased use of flexible manufacturing systems (FMS) efficiently to provide customers with diversified products has created a significant set of operational challenges. Although extensive research has been conducted on design and operational problems of FMS, many problems remain unsolved. To improve the efficiency of FMS, the optimized model of FMS was proposed based on hybrid genetic algorithms (HGA), and then we introduce the basic procedure and genetic operation of HGA. Finally, an illustration of the optimized model shows that the solution quality by the HGA is better than that by genetic algorithms (GA). Traditional GA is usually of low efficiency because of its early convergence, however, the optimized HGA not only inherits GA's global optimization feature, but also can avoid premature convergence, and improve the efficiency greatly.