A Novel Approach to Supply the Water Reservoir Demand Based on a Hybrid Whale Optimization Algorithm

Abstract

Managing water resources requires the optimum operation of dam reservoirs. To satisfy the downstream water demand in the operational optimization of Boostan dam reservoir, the improved whale optimization algorithm (IWOA) performance was compared in the present study with that of its constituents (i.e., the whale optimization and differential evolution) based on GAMS nonlinear programming results. The model evaluative indicators and an objective function were used to select the optimal algorithm. The findings suggested that IWOA resulted in the lowest computational duration and fastest convergence rate compared to the other algorithms. Additionally, the average water demand and discharge volume of IWOA were 3.21 × 106 m3 and 3.03 × 106 m3, respectively. In contrast, the other algorithms yielded lower water release volumes. IWOA enhanced the WOA performance by 21.7% through reducing the variation coefficient by 78% in optimizing the objective function. The water demand was therefore more effectively satisfied by the IWOA compared to the other algorithms. Furthermore, the IWOA resulted in a lower amount of errors. The hybrid algorithm performance increased in terms of all the evaluative indicators. Developing multicriteria decision-making models using TOPSIS and the Shannon entropy also suggested the IWOA excels the other algorithms in optimizing the reservoir operational problem.

Investigating dam reservoir operation optimization using metaheuristic algorithms

“…which means that it has the lowest capability to recover and return to normal operation in the case of a system failure (Sharifi et al 2021;Donyaii et al 2020). The most resilient model is determined to be WOA, as it has the best CV.…”

Optimization of Cascade Reservoir Operation for Power Generation, Based on an Improved Lightning Search Algorithm

“…Mixing different algorithms could help overcome the shortcomings of a single algorithm and solve problems more efficiently [23]. The improved algorithms of these algorithms are hybrid whale optimization algorithm [30], hybrid algorithm of invasive weed optimization and cuckoo search algorithm [23], hybrid slime mold and arithmetic optimization algorithm [31], and so on. These are widely used in reservoir optimal operation problems, including short-term [32,33], medium-and long-term optimal operation [34][35][36].…”

Position Deployment Optimization of Maneuvering Conventional Missile Based on Improved Whale Optimization Algorithm

“…The experimental results show that the improved algorithm has better performance. Donyaii et al [21] improved WOA for water resource management and reservoir operation and analyzed water resource management problems using WOA. Bozorgi and Yazdani [22] improved WOA by combining WOA with differential evolution (DE) to solve the premature convergence problem of WOA and verified the performance of the improved algorithm through experiments.…”