A genetic algorithm with Tabu Search for multi-objective scheduling constrained flexible job shop

A hybrid algorithm is proposed to solve scheduling problems in flexible production environment, where time, cost and equipment utilization rate are all concerned. Firstly, the scheduling model is built; the scheduling precedence is determined by the representation based operation. Objective dimensions can be unified by standardization principle. Secondly, AHP application is adopted to translate multi-objective into single objective problem. In order to avoid the premature convergence of simple GA, it combines the advantage of global search ability of GA with the self-adaptive merit of Tabu Search (TS). The result of the test shows that this method is feasible and efficient.