Comparison of evolutionary algorithms applied to optimal design of water distribution networks

Abstract

ABSTRACT The pursuit of efficient water distribution network (WDN) projects that reflect the complexities of real systems has spurred the development and application of various optimization techniques. Among these, multi and many-objective optimization hold particular significance due to the intrinsic interplay between variables within water distribution networks. Within this domain, evolutionary algorithms have emerged as a promising optimization option, offering a range of methodologies documented in the literature. To systematically evaluate these approaches, a methodology was devised to compare six evolutionary algorithms in the context of water distribution networks optimization: NSGA-II, NSGA-III, U-NSGA-III, R-NSGA-III, MOEA/D, and RVEA, using two distinct objective functions. The comparative analysis utilized as key metrics the efficiency criteria (E), cumulative distribution function (CDF), error statistics and algorithm complexity. The findings revealed that while most algorithms successfully converged to the known global optimum of the employed case study, NSGA-II and NSGA-III exhibited superior performance, notably in minimizing costs. These results demonstrate the efficacy of these algorithms in tackling the complexities inherent in water distribution networks optimization, positioning them as leading contenders in this field.

Keywords

• Water distribution networks
• Optimization
• Multi-objective
• Many-objective
• Evolutionary algorithms