Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/80334
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Type: Journal article
Title: Self-adaptive differential evolution algorithm applied to water distribution system optimization
Author: Zheng, F.
Zecchin, A.
Simpson, A.
Citation: Journal of Computing in Civil Engineering, 2013; 27(2):148-158
Publisher: ASCE-Amer Soc Civil Engineers
Issue Date: 2013
ISSN: 0887-3801
1943-5487
Statement of
Responsibility: 
Feifei Zheng, Aaron C. Zecchin and Angus R. Simpson
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 because 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: (1) 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; (2) 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 (3) 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 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.
Keywords: Optimization; Differential evolution; Water distribution systems.
Rights: © 2013 American Society of Civil Engineers.
RMID: 0020126507
DOI: 10.1061/(ASCE)CP.1943-5487.0000208
Appears in Collections:Civil and Environmental Engineering publications

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