Pareto-based discrete harmony search algorithm for flexible job shop scheduling

This paper proposes a pareto-based discrete harmony search (PDHS) algorithm to solve multi-objective FJSP. The objectives are the minimization of two criteria namely, the maximum of the completion time (Makespan) and the mean earliness and tardiness. Firstly, we develop a new method for the initial the machine assignment task. Some existing heuristics are also employed for initializing the harmony memory. Hence, harmony memory is filled with discrete machine permutation for machine assignment and job permutation for operation sequence. Secondly, we develop a new rule for the improvisation to produce a new harmony for FJSP. The machine assignment and operation sequence are processed respectively. Thirdly, several local search methods are embedded to enhance the algorithm's local exploitation ability. Finally, extensive computational experiments are carried out using well-known benchmark instances. Computational results and comparisons show the efficiency and effectiveness of the proposed pareto-based discrete harmony search algorithm for solving the multi-objective flexible job-shop scheduling problem.