Self-Adaptive Differential Evolution Algorithm Applied to Water Distribution System Optimization

Abstract

Differential evolution (DE) is a relatively new technique that has recently been used to optimize the design for water distribution systems (WDSs). Several parameters need to be determined in the use of DE, including: population size, N; mutation weighting factor, F; crossover rate, CR and a particular mutation strategy. It has been demonstrated that the search behavior of DE is especially sensitive to the F and CR values. These parameters need to be fine-tuned for different optimization problems as they are generally problem-dependent. A self-adaptive differential evolution (SADE) algorithm is proposed to optimize the design of WDSs. Three new contributions are included in the proposed SADE algorithm: (i) instead of pre-specification, the control parameters of F and CR are encoded into the chromosome of the SADE algorithm and hence are adapted by means of evolution; (ii) F and CR values of the SADE algorithm apply at the individual level rather than the generational level normally used by the traditional DE algorithm; and (iii) a new convergence criterion is proposed for the SADE algorithm as the termination condition, thereby avoiding pre-specifying a fixed number of generations or computational budget to terminate the evolution. Four WDS case studies have been used to demonstrate the effectiveness of the proposed SADE algorithm. The results obtained show that the proposed algorithm exhibits good performance in terms of solution quality and efficiency. The advantage of the proposed SADE algorithm is that it reduces the effort required to fine-tune algorithm parameter values.

Lost in Optimisation of Water Distribution Systems? A Literature Review of System Design

“…The following four variants of DE algorithm are used: (i) the SDE algorithm with fixed mutation (F) and crossover (CR) parameter values; (ii) the dither DE (dDE) variant [279] with the randomised F; (iii) the modified dDE (MdDE) variant with the randomised F and CR; (iv) the SADE variant [173] with the self-adapted F and CR along the searching progress. The modified DE is proposed specifically for this study.…”

Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms

“…The WDN of Hanoi in Vietnam [34] is the first case study. This academic benchmark has been used in several works [35,36], where the objective was either to design the network or to optimize the operations performed within it. It consists of one reservoir, 31 demand nodes and 34 pipes, as shown in Figure 1a.…”

Sensor Placement for Leak Location in Water Distribution Networks using the Leak Signature Space

“…First, the WDN of Hanoi in Vietnam (Fujiwara and Khang, 1990). This academic benchmark has been used in several works, where the objective was either to design the network or to optimize the operations performed within it (Zheng and Simpson, 2013). It consists of 1 reservoir, 31 demand nodes and 34 pipes as shown in Figure 1.a.…”