Abstract:
Genetic algorithms are nature based stochastic computational techniques. The major advantages of these algorithms are their broad applicability, flexibility and the potential of finding near optimal solutions. The paper presents a methodology based on genetic algorithm for lower cost design of new, and augmentation of existing water distribution networks. The results have been compared with a nonlinear programming technique through their application in a case study. The genetic algorithm results in improved convergence in successive generations leading to lower cost solution. Parameters governing the convergence of solution in nonlinear and genetic algorithm have also been discussed.
