Self-Adaptive Cuckoo Search Algorithm for Optimal Design of Water Distribution Systems

B. Sriman Pankaj (), M. Naveen Naidu (), A. Vasan () and Murari RR Varma ()
Additional contact information
B. Sriman Pankaj: BITS Pilani, Hyderabad Campus
M. Naveen Naidu: BITS Pilani, Hyderabad Campus
A. Vasan: BITS Pilani, Hyderabad Campus
Murari RR Varma: BITS Pilani, Hyderabad Campus

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2020, vol. 34, issue 10, No 5, 3129-3146

Abstract: Abstract Self-adaptive cuckoo search algorithm is used to optimize the design of water distribution system problems. It is proposed to dynamically adjust the two sensitive parameters of the algorithm, (i) step size control parameter ‘α’ and (ii) discovering probability parameter ‘Pa’ which largely govern the exploration and exploitation search strategies of the algorithm. These parameters are essential for enhancing the performance of the algorithm and normally the values of these parameters needs careful selection according to the type of problem. Single objective self-adaptive cuckoo search algorithm (SACSA) and multi-objective self-adaptive cuckoo search algorithm (SAMOSCA) are proposed in this study. Robustness and efficiency of these algorithms in single (minimization of cost) and multi-objective scenarios (minimization of cost and maximization of resilience) is validated using standard water distribution benchmark problems i.e. Two loop and Hanoi network. These are later applied to solve a medium size real-life water distribution system located at Pamapur, Telangana, India. A simulation-optimization based program combining the water distribution network simulation software EPANET 2.2 and MATLAB is used for computation. The proposed methodology has provided better results in terms of computational efficiency as well as found better solutions when compared to the previously reported results in both single and multi-objective scenarios. In the case of multi-objective problems, it has been observed that SAMOCSA has been able to find new points in pareto front when compared to the best-known pareto front reported in the literature. Self-adaptive cuckoo search algorithm has been found to be an attractive alternative in both exploration and exploitation of larger search spaces for finding better optimal solutions.

Keywords: Cuckoo search; Multi-objective optimization; Pamapur WDS; Self-adaptive; Water distribution system (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s11269-020-02597-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:34:y:2020:i:10:d:10.1007_s11269-020-02597-2

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-020-02597-2

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().