01557nas a2200193   4500008004100000245013800041210006900179260000900248300001400257490000700271520080600278653002201084653004101106653004701147653002501194100001301219700001401232856011701246       2013                        eng d00aParameters selection in the discrete particle swarm optimization algorithm solving gate and runway combinational optimization problem0 aParameters selection in the discrete particle swarm optimization  c2013  a197 - 2010 v113 aGate 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.10aAirport operation10aDiscrete particle swarm optimization10aGate and runway combinational optimization10aParameters selection1 aDing, J.1 aZhang, Y.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84880782704&partnerID=40&md5=b89c7c4e42430962155e9283216c7b70