A Methodology to Improving the Performance of MOAHA Optimization Algorithm using Chaos Theory; Principle and Application in Optimal Reservoir Operation

Zahra Khoramipoor () and Saeed Farzin ()
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Zahra Khoramipoor: Semnan University
Saeed Farzin: Semnan University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2025, vol. 39, issue 6, No 18, 2819-2840

Abstract: Abstract This study introduces a novel algorithm, CMOAHA, which integrates the multi-objective hummingbird optimizer with chaos theory to optimize multi-reservoir system management. The algorithm aims to maximize hydropower energy production and minimize evaporation losses. The performance of CMOAHA is compared to that of MOGWO, MOALO, and NSGA-II algorithms. Using evaluation criteria such as MS, CV, and MID, CMOAHA demonstrates superior efficiency, achieving values of CV = 4,834,269.468, MS = 19,359,123.542, and MID = 6,895,142.911. In contrast, the gray wolf optimizer (MOGWO) shows the lowest performance, with CV = 17,602,966.401 and MID = 17,429,422.893. Rankings confirm that the improved hummingbird algorithm achieves the highest efficiency, with a rating of 0.95, while NSGA-II ranks lowest. Moreover, the output of the CMOAHA algorithm closely aligns with results from LINGO software, achieving a 96.73% match to the global optimum. These findings highlight the enhanced performance and strong capabilities of the hummingbird algorithm when augmented with chaos theory. The results showed that the multi-objective artificial hummingbird algorithm enhanced by chaos theory provides better accuracy and certainty compared to other algorithms. Graphical Abstract

Keywords: Chaos theory; Reservoir operation; Cascade multi-purpose reservoirs; Hydropower energy; MOAHA algorithm (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11269-025-04092-y

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