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Comparative Performance of Recent Advanced Optimization Algorithms for Minimum Energy Requirement Solutions in Water Pump Switching Network

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Abstract

The present work explores the qualitative and quantitative comparative analysis of nine recently developed meta-heuristic algorithms for the optimization of water pump switching problem. Heat transfer search algorithm, Water wave optimization, Ant lion optimizer, Symbiotic organisms search algorithm, Artificial Bee Colony algorithm, Cuckoo search algorithm, Passing vehicle search, Biogeography based optimization, and Sine–cosine algorithm are considered in the present work. A statistical analysis of the results are carried out to identify the statistical significant between the results of comparative algorithms. The effect of various constraint handling techniques on the performance of the algorithms are also identify and presented. A set of the alternative solutions for the minimum energy requirement are obtained for the best algorithm and presented. The solutions for the different number of pump in operation for best performing algorithm are also obtained and presented. Finally, the convergence of the considered algorithm in obtaining the minimum energy solutions are presented and discussed.

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Abbreviations

E :

Pumping energy (kW)

Q :

Flow rate (m3/s)

P :

Pump pressure (bar)

x :

Binary variable

n :

Pumping station

m :

Pump

η :

Motor-pump efficiency

γ:

Specific weight (kg/m3)

L :

Lower limit

U :

Upper limit

D :

Discharge

L :

Pressure loss

S :

Suction

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Authors and Affiliations

  1. Department of Mechanical Engineering, School of Technology, Pandit Deendayal Petroleum University, Gandhinagar, Gujarat, India

    Vivek K. Patel

  2. Department of Mechanical Engineering, Indus University, Ahmedabad, Gujarat, India

    Bansi D. Raja

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Patel, V.K., Raja, B.D. Comparative Performance of Recent Advanced Optimization Algorithms for Minimum Energy Requirement Solutions in Water Pump Switching Network. Arch Computat Methods Eng 28, 1545–1559 (2021). https://doi.org/10.1007/s11831-020-09429-x

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