Performance Study of Differential Evolution with Various Mutation Strategies Applied to Water Distribution System Optimization

摘要

Differential evolution (DE) is a relatively new optimization technique that has been employed to optimize the design of water distribution systems (WDSs). There are three important operators involved in the use of DE: mutation, crossover and selection. These operators are similar to the commonly used genetic algorithms (GAs). However, DE differs significantly from GAs in that mutation is an important operator for DE, while in contrast, crossover is an important operator for GAs. It has been found that the success of the DE algorithm in solving different mathematical optimization problems crucially depends on the mutation strategy that is used. This paper aims to investigate the relative effectiveness of five frequently used mutation strategies of DE when applied to WDS optimization. The five DE variants with different mutation strategies are applied to two well-known WDS case studies: the New York Tunnels Problem and the Hanoi Problem.