Pipe Network Optimization Using Copmact Genetic Algorithm

This paper presents an application of compact genetic algorithm (CGA) to pipe network optimization problem. Compact genetic algorithm is recently proposed to reduce the storage and computational requirement of the population – based GAs. Compact GA acts like a standard GA with binary chromosome and uniform crossover but dose not use a population. Instead the GGA represents a represent a virtual population for a binary GA by a vector of probability representing the change that the optimal solution has one at each bit position. The application of the CGA to pipe network optimization problem is considered in this paper and the result are presented for two benchmark examples and compared with the exiting solutions in the literature . the results show the ability of the CGA to locate optimal solution of the problem considered with a computational effort comparable to the improved population-based GAs and much less storage requirement.