Sorting

Operating system

Algorithm

Multi-swarm optimization

Mathematical optimization

Geodesy

Pareto principle

Test functions for optimization

Evolutionary algorithm

Benchmark (surveying)

Geography

Mathematics

Computer science

Mode (computer interface)

Multi-objective optimization

Differential evolution

Particle swarm optimization

Genetic algorithm

Ain Shams Engineering Journal

In this paper, the application of three well-known multi-objective optimization algorithms to water distribution network (WDN) optimum design has been considered. Non-dominated sorting genetic algorithm II (NSGA-II), Multi-objective differential evolution (MODE) and Multi-objective particle swarm optimization (MOPSO) algorithms are applied to benchmark mathematical test function problems for evaluating the performance of these algorithms. The Accuracy and computational runtime are the two indicators used for the comparison of these three algorithms. The optimization results of mathematical test functions show that all three algorithms were able to accurately produce Pareto Front, but the computational time of MODE algorithm to achieve the optimal solutions is lower than the two other algorithms. Then, the discussed algorithms have been used to optimize the WDN design problem. Comparison of the generated solutions on the Pareto Front for WDN design shows that the obtained Pareto Front of MODE is more accurate and faster.

Comparison of evolutionary multi objective optimization algorithms in optimum design of water distribution network