Constraint satisfaction-based hybrid algorithm for Job-Shop scheduling problem with parallel machines
约束满足混合算法求解并行机Job-Shop调度问题

Analyzed the Job-Shop scheduling problem with parallel machines and established its constraint satisfaction optimization model. Proposed a hybrid optimization algorithm combined with constraint satisfaction and variable neighborhood search technique. In the algorithm, chosen a variable and assigned by variable ordering and value ordering method. Resolved resource conflicts using backtracking and obtained constraint propagation technology until a feasible schedule. Then the feasible schedule acted as an initial solution of the variable neighborhood search algorithm. Enhanced the convergence through local search technology and improved the quality of solution through the diversity of the designed neighborhood structures according to the characteristics of the problem. The feasibility and validity of the proposed hybrid method is demonstrated by the data experiment compared with the other two algorithms.