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This paper presents an investigation on the efficacy of particle swarm optimization (PSO) and genetic algorithm (GA), two popular global optimization algorithms to solve complex optimization problems, for the second order design (SOD) - a process of selecting optimal baseline configuration, in a GPS network while satisfying the desired precision criteria at minimal cost. The algorithms are tested on a six-point GPS network established within IIT Kanpur campus. The results have shown that the PSO has yielded better results than the GA in solving the SOD problem.

A comparison of particle swarm optimization (PSO) and genetic algorithm (GA) in second order design (SOD) of GPS networks