Parameters selection in the discrete particle swarm optimization algorithm solving gate and runway combinational optimization problem

Gate and runway combinational optimization (GRCO) problem is of great significance in airport operation. In this paper, experimental analysis is performed on the parameters characteristics of the discrete particle swarm optimization (DPSO) algorithm for combinatorial optimization problems. Inertia weight, acceleration constants and population size all have an important impact on the performance of the algorithm. Optimal values exist in the specific application of the respective parameters. The optimal value interval of the population size does not vary with different acceleration constants when inertia weight is constant. Increasing the population size can improve the solution quality, but the time overhead increases significantly. Finally, each parameters selection guidelines are provided.