Hybrid Intelligent Algorithm for Optimization Design of Annular Water Supply Network

One hybrid intelligent algorithm is designed to solve the annular water supply network optimization. The model to minimize the objective function of the annual reduced cost with the constraints of hydraulic conditions. The intelligent optimization algorithm population based incremental learning - PBIL based on probability learning strategy is combined to particle swarm optimization algorithm-PSO. The probability matrix in PBIL algorithm is modified with the quick velocity update strategy of PSO algorithm. An integer encoding representation is given according to the water supply network problem. Also, information entropy is adopted to reduce the algorithm´s complexity and estimate the convergent tendency. The modified intelligent evolutionary algorithm is tested on engineering projects and compared with genetic algorithm. The good adaptability, validity and stability performance are fully shown by the results.