A genetic algorithm was developed to optimize the spatial layout of military command centres. This paper describes a simulation experiment in which the impact of key algorithm parameters on its search efficiency was examined. The results confirmed the benefit of a large population size and a long evolution process for improving the search effectiveness. For the parameter that controls the rate of introducing new solutions (i.e., probability of swap), a medium level configuration was found to be superior. Results of this study provide guidelines and heuristics for configuring key parameters of the proposed algorithm so that its search efficiency and computational expense are best balanced.
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