Optimal Design of a Water Supply System Based on Improved Self-adaptive Particle Swarm Algorithm

For the problem of easily getting in the local minimum and difficulty in finding the optimal solution when the water supply system are optimized by the particle swarm optimization (PSO) , the paper proposes a modified dynamically adaptive particle swarm optimization (M-DAPSO) . By defining the convergence factor and parameter adjustment function, the improved algorithm proposes the adaptive mutation strategy to increase the population diversity and adjust its parameters. The algorithm is finally applied to Hanoi network optimization. Result show that it can obtain the optimum cost by the minimum computational cost. Compared with other optimization algorithms, M-DAPSO has stronger ability of searching globally and faster convergence speed.