A Hybrid Artificial Bee Colony Algorithm with Local Search for Flexible Job-shop Scheduling Problem

This paper presents a hybrid artificial bee colony algorithm for solving the flexible job-shop scheduling problem (FJSP) with the criteria to minimize the maximum completion time (makespan). In solving the FJSP, we have to focus on two sub-problems: determining the sequence of the operations and selecting the best machine for each operation. In the proposed algorithm, first, several dispatching rules and the harmony search algorithm are used in creating the initial solutions. Thereafter, one of the two search techniques is randomly selected with a probability that is proportional to their fitness values. The selected search technique is applied to the initial solution to explore its neighborhood. If a premature convergence to a local optimum happens, the simulated annealing algorithm will be employed to escape from the local optimum. Otherwise, the filter and fan algorithm is utilized. Finally, the crossover operation is presented to enhance the exploitation capability. Experimental results on the benchmark data sets show that the proposed algorithm can effectively solve the FJSP.