Multi-level job scheduling in a flexible job shop environment

This study deals with a scheduling problem with multi-level job structures in a flexible job shop environment. This scheduling process arises after the part production plans are created by the MRP (material requirement planning) system, therefore the total tardiness measure is considered as an objective function in order to complete the parts by the set due dates. MILP (mixed integer linear programming) model is introduced to mathematically represent the target problem. Owing to the high complexity of the target problem, GA (genetic algorithm) is proposed to solve the problem and additional methods, such as priority rules and local search rules, are applied to improve the performance of GA. Computational examples are shown and the results are discussed in comparison with the results of IBM ILOG CPLEX and IBM ILOG CP Optimizer.