A novel parallel multiobjective genetic algorithm and its application in process scheduling

This paper proposes a parallel multiobjective genetic algorithm to solve process scheduling problems with the characteristics of multiobjectives, hybrid dynamics and real time computation. An objective ranking evaluation technique is developed to associate the trade-off information to a better solution with preference articulation. A novel double-layer chromosome coding method is used to express the system hybridness. Computation time is at least reduced to 10 percent of its original value by adopting a hierarchical decomposed parallel computing technique. Simulation results show that the algorithm illustrated has prospective applications to complex process scheduling optimization problems.