A new strategy of chaotic PSO and its application in optimization design for pipe network

Two drawbacks of Chaotic Particle Swarm Optimization (CPSO) are analyzed in the paper, the first one is the search in the initial state is helpless and the second is it is ineffective in jumping out of the local optimum at the later stage. An improved strategy of CPSO (HMCPSO) is introduced to modify these problems. This method uses the randomness, ergodicity and regularity of chaos to associates with PSO to improve the abilities of jumping out of local optimum and searching for the global optimum. Besides, the mechanism of judging the historical data of particles´ location is proposed, by using which the excess operations of chaotic processes and the run time are reduced significantly. At the end, HMCPSO is applied in the optimization design of pipe network, the result shows the algorithm finds a lower cost point and the reliability is satisfactory.