The performance of the proposed particle swarm optimization algorithm is tested by random experiments. The experimental results show that the average deviation between the proposed PSO and the optimal ...

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Alireza Sahebgharani, MULTI-OBJECTIVE LAND USE OPTIMIZATION THROUGH PARALLEL PARTICLE SWARM ALGORITHM, Journal of Urban and Environmental Engineering, Vol. 10, No. 1 (January to June 2016), pp. 42-49 ...

It also stressed that the algorithm has a tracking efficiency of 97.54%, which compares to 95.56% for the grasshopper optimization algorithm (GOA), 94.27% for particle swarm optimization (PSO), 91 ...