A novel self-adaptation and sorting selection-based differential evolutionary algorithm applied to water distribution system optimization

Abstract The differential evolution (DE) algorithm has been demonstrated to be the most powerful evolutionary (EA) optimally design water distribution systems (WDSs), but issues such as slow convergence speed, limited exploratory ability, and parameter adjustment remain when used for large-scale WDS optimization. This paper proposes a novel self-adaptation sorting selection-based (SA-SSDE) that can solve optimization problems more efficiently while having greater ability explore global optimal solutions. following two unique features enable better performance of proposed SA-SSDE algorithm: (1) DE/current-to-pbest/n mutation selection operators are speed up thus improve efficiency; (2) adaptation strategy in JADE (an adaptive by Zhang & Sanderson 2009) is introduced modified cater optimization, it capable dynamically adapting control parameters (i.e., F CR values) fitness landscapes characteristic larger-scale problems, allowing ability. found new best solutions $7.068 million, €1.9205 $30.852 million three well-known large networks (ZJ164, Balerma454, Rural476), 1.02, 1.92, 5.99 times faster than classic DE, respectively. Investigations into searching behavior during carried out, resulting understanding why outperforms well guidance developing advanced EAs.