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

摘要

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 bui 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.