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

Author

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  • 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)

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.

Suggested Citation

  • B. Sriman Pankaj & M. Naveen Naidu & A. Vasan & Murari RR Varma, 2020. "Self-Adaptive Cuckoo Search Algorithm for Optimal Design of Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3129-3146, August.
  • Handle: RePEc:spr:waterr:v:34:y:2020:i:10:d:10.1007_s11269-020-02597-2
    DOI: 10.1007/s11269-020-02597-2
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    References listed on IDEAS

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    1. Tiku T. Tanyimboh & Anna Czajkowska, 2018. "Self-Adaptive Solution-Space Reduction Algorithm for Multi-Objective Evolutionary Design Optimization of Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3337-3352, August.
    2. Salman, Ayed & Engelbrecht, Andries P. & Omran, Mahamed G.H., 2007. "Empirical analysis of self-adaptive differential evolution," European Journal of Operational Research, Elsevier, vol. 183(2), pages 785-804, December.
    3. Salah Saleh & Tiku Tanyimboh, 2014. "Optimal Design of Water Distribution Systems Based on Entropy and Topology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3555-3575, September.
    4. Hossein Fallah & Ozgur Kisi & Sungwon Kim & Mohammad Rezaie-Balf, 2019. "A New Optimization Approach for the Least-Cost Design of Water Distribution Networks: Improved Crow Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3595-3613, August.
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    Cited by:

    1. Priyanshu Jain & Ruchi Khare, 2021. "Application of Parameter-Less Rao Algorithm in Optimization of Water Distribution Networks Through Pressure-Driven Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 4067-4084, September.
    2. Arya Yaghoubzadeh-Bavandpour & Omid Bozorg-Haddad & Mohammadreza Rajabi & Babak Zolghadr-Asli & Xuefeng Chu, 2022. "Application of Swarm Intelligence and Evolutionary Computation Algorithms for Optimal Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2275-2292, May.
    3. Mashor Housh & Alaa Jamal, 2022. "Utilizing Matrix Completion for Simulation and Optimization of Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(1), pages 1-20, January.

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