@ARTICLE{Sulianto_Optimization_2021, author={Sulianto and Setiono, Ernawan and Yasa, I Wayan}, number={No 48}, journal={Journal of Water and Land Development}, pages={55-64}, howpublished={online}, year={2021}, publisher={Polish Academy of Sciences Committee on Agronomic Sciences Section of Land Reclamation and Environmental Engineering in Agriculture; Institute of Technology and Life Sciences}, abstract={Under conditions of gravity flow, the performance of a distribution pipe network for drinking water supply can be measured by investment cost and the difference in real and target pressures at each node to ensure fairness of the service. Therefore, the objective function for the optimization in the design of a complex gravity flow pipe network is a multi-purpose equation system set up to minimize the above-mentioned two parameters. This article presents a new model as an alternative solution to solving the optimization equation system by combining the Newton–Raphson and genetic algorithm (GA) methods into a single unit so that the resulting model can work effectively. The Newton–Raphson method is used to solve the hydraulic equation system in pipelines and the GA is used to find the optimal pipe diameter combination in a net-work. Among application models in a complex pipe network consisting of 12 elements and 10 nodes, this model is able to show satisfactory performance. Considering variations in the value of the weighting factor in the objective function, opti-mal conditions can be achieved at the investment cost factor (ω1) = 0.75 and the relative energy equalization factor at the service node (ω2) = 0.25. With relevant GA input parameters, optimal conditions are achieved at the best fitness value of 1.016 which is equivalent to the investment cost of USD 56.67 thous. with an average relative energy deviation of 1.925 m.}, title={Optimization model the pipe diameter in the drinking water distribution network using multi-objective genetic algorithm}, type={Article}, URL={http://journals.pan.pl/Content/119048/PDF/Sulianto%20et%20al%20698.pdf}, doi={10.24425/jwld.2021.136146}, keywords={diameter, genetic algorithm, network, Newton–Raphson method, optimum, pipe}, }