PSOSA: An Optimized Particle Swarm Technique for Solving the Urban Planning Problem
暂无分享,去创建一个
This paper introduces an optimized particle swarm technique (PSOSA) that uses simulated annealing for optimizing the inertia weight. To study the performance of the proposed technique, it has been applied on the urban planning problem involving a multi-objective fitness function that includes non-overlapping constraints as well as relative positioning requirements. Results show that the proposed technique performs much better as regards convergence speed as well as sustainability to increased load of growing number of blocks to be fitted in the urban planning problem
[1] James Kennedy,et al. Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.
[2] G. Franck,et al. Evolutionary Algorithms in Urban Planning , 2001 .
[3] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.