Optimization of urban water pipe network design using fast-messy genetic algorithms (fmGA)

Abstract To have an efficient water distribution network, optimal design alternatives need to be identified and analysed using combined hydraulic modelling optimization. This paper reports on the application of fast-messy genetic algorithm (fmGA) coupled with tool EPANET assess select optimum operational alternative for a pipe network. The sole objective optimization was minimize network costs subject constraints. fmGA first tested benchmark case study Hanoi then applied real Maun, Botswana which is considered as study. We compared our results model other techniques findings test revealed that superior popular metaheuristic methods in terms processing speed comparable accuracy pressure constraints fulfilled all nodes. It also provides best least solution. For pipeline configuration route were determined, Configuration B found cost solution improve supply situation Maun.