A new artificial bee colony algorithm for the flexible job shop scheduling problem with extra resource constraints in numeric control centers

This paper tackles a flexible job shop scheduling problem with extra resource constraints (FJSP-ERC) which arises in the practical context of aircraft manufacturing. The challenge is to schedule operations on identical computer numerical control (CNC) machining centers, considering the simultaneous availability of machines and tools. We describe the FJSP-ERC as a mixed integer linear programming (MILP) model and then propose an efficient meta-heuristic algorithm ABC II to solve the scheduling problem. This is a novel structured artificial bee colony algorithm incorporated with problem-specific local improvement strategies organized by Adaptive Large Neighborhood Search (ALNS). After applying the initialization techniques to the solution, the main structure of the algorithm is designed in two stages. In the first stage, all machining operations of a part are taken as a whole in order to find some near-optimal job order. The solutions obtained in the first stage will then serve as a warm-up for the second stage, where the operations are treated as independent individuals. After preliminary parameter tuning, comprehensive computational experiments were conducted to verify the effectiveness of the proposed solution approach by comparing with the solutions obtained by five different algorithms and CPLEX. The results show that the proposed ABC II significantly outperforms other methods in terms of efficiency and effectiveness.