Estimating the transpiration of kiwifruit using an optimized canopy resistance model based on the synthesis of sunlit and shaded leaves by Zongyang Li, Lu Zhao, Zhengxin Zhao, Huanjie Cai, Liwen Xing, Ningbo Cui

“…This study established a rc estimation model based on a synthesis of sunlit and shaded leaves (SSL) and optimized it using Ant Colony Optimization (ACO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). …”
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Engineering oriented shape optimization of GHT-Bézier developable surfaces using a meta heuristic approach with CAD/CAM applications by Samia BiBi, Md Yushalify Misro, Muhammad Abbas, Asnake Birhanu, Kenjiro T. Miura, Mohd Nadhir Ab Wahab, Emad E. Mahmoud

“…This Grey Wolf optimization algorithm impersonates the hunting tactics of grey wolves in nature. …”
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Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems by Mohammad Aljaidi, Pradeep Jangir, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Ali Fayez Alkoradees, Arpita, Aseel Smerat

“…The FATA algorithm is evaluated against recently developed and improved optimization techniques, such as rime-ice formation phenomenon based Improved RIME (IRIME) Algorithm, Newton–Raphson-Based Optimization (NRBO), Resistance Capacitance Algorithm (RCA), Krill Optimization Algorithm (KOA), and Grey Wolf Optimizer (GWO), across multiple optimization objectives: reduction in generation cost, reduction in power loss and combined generation cost plus power loss, termed as Gross cost function. …”
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An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young’s double-slit experiment algorithm by Basma S. Alqadi, Deema Mohammed Alsekait, Mohamed F. Issa, Essam H. Houssein, Fatma H. Ismail, Mokhtar Said, Nour Mostafa, Fahmi Elsayed

“…The proposed method integrates the YDSE algorithm with five other metaheuristic techniques: the sine cosine Algorithm (SCA), moth flame optimization (MFO), Harris Hawk optimization (HHO), gray wolf optimization (GWO) and chimp optimization Algorithm (ChOA) to estimate six critical parameters of PEMFC. …”
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Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment by Pei Zhu, Shize Jiang, Jiangao Zhang, Ziheng Xu, Zhi Sun, Quan Shao

“…In this process, the study considers only the use of fire-extinguishing balls as the fire suppressant for the UAVs. The improved multi-population grey wolf optimization (MP–GWO) algorithm and non-Dominated sorting genetic algorithm II (NSGA-II) were designed to solve the path planning and task allocation models, respectively. …”
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Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making by Guanquan Zhu, Minyi Ye, Xinqi Yu, Junhao Liu, Mingju Wang, Zihang Luo, Haomin Liang, Yubin Zhong

“…Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. …”
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CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

“…Moreover, the performance of IHO was proven to be optimal compared to HO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and Sparrow Search Algorithm (SSA) by calculating twelve test functions. …”
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Optimum Design of a Photovoltaic Inverter System Based on Ga, Pso and Gwo Algorithms with a Mppt Sliding Mode Control by Alberto Coronado-Mendoza, Mónica Camas-Náfate, Jesús Sergio Artal-Sevil, José Antonio Domínguez-Navarro

“…Furthermore, eight system parameters are optimized using advanced techniques such as genetic algorithms, particle swarm optimization, and gray wolf optimization. …”
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Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

“…Abstract This study presents a comparative analysis of hybrid Extreme Learning Machine (ELM) models optimized with metaheuristic algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO) for real-time Rate of Penetration (ROP) prediction in drilling operations. …”
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Dynamic Economic Dispatch of Power System Network Having Thermal Units and Electric Vehicles using IGWO by Anjali Jain, Ashish Mani, Anwar Siddiqui

“…In the presented paper,  Improved Grey Wolf Optimizer (IGWO) is proposed to solve this complex problem. …”
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A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and... by Priya Mathur, Hammad Shaikh, Farhan Sheth, Dheeraj Kumar, Amit Kumar Gupta

“…The research analyzed fourteen predictive models, employing advanced hyperparameter optimization methods facilitated by Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). …”
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Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy by T. Yuvaraj, T. Sengolrajan, Natarajan Prabaharan, K. R. Devabalaji, Akie Uehara, Tomonobu Senjyu

“…A hybrid improved grey wolf optimization-particle swarm optimization (IGWO-PSO) algorithm is developed to solve this complex optimization problem. …”
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Smart homes energy management: Optimal multi-objective appliance scheduling model considering electrical energy storage and renewable energy resources by Moslem Dehghani, Seyyed Mohammad Bornapour

“…The maximum standard deviation of total objective function between all cases for IBBO, gray wolf optimizer (GWO), and whale optimization algorithm (WOA) are 6.55, 17.22, and 24.87, respectively, which show the robustness of IBBO in finding the best solution in comparisons of other algorithms. …”
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Comprehensive Fault Location on Transmission Lines Considering Variation in Line Parameters and Saturation in Current Transformers by Duy C. Huynh, Loc D. Ho

“…Numerical results and comparisons confirm the proposal’s effectiveness, being better than the previous traditional fault location technique such as the impedance-based (IB) technique, as well as other meta-heuristic algorithms such as a grey wolf optimization (GWO) algorithm, a gravitational search (GS) algorithm, and an inclined planes optimization (IPO) algorithm. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…The study compared the performance of five optimization algorithms: Grey Wolf Optimizer (GWO), Artificial Hummingbird Algorithm (AHA), Tunicate Swarm Algorithm (TSA), War Strategy Algorithm (WSA), and Moth flam optimizer (MFO). …”
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Water Quality Prediction Based on Hybrid Deep Learning Algorithm by Bhagavathi Perumal, Niveditha Rajarethinam, Anusuya Devi Velusamy, Venkatesa Prabhu Sundramurthy

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A novel economic load dispatch method of microgrid based on hybrid slime mould and genetic algorithm by Wei Ba, Wei Sun, Chunjiang Zhao, Qi Li

“…For performance evaluation, GSMA is compared with slime mould algorithm (SMA), grey wolf optimizer (GWO), sparrow search algorithm (SSA), Harris Hawks optimization (HHO), whale optimization algorithm (WOA) and particle swarm optimization (PSO) using standard optimization functions. …”
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Enhancing network lifetime in WSNs through coot algorithm-based energy management model by Namita Shinde, Dr. Vinod H․ Patil

“…This addresses issues such as high energy consumption, communication delays, and security.To ensure energy savings and network reliability, the fitness function evaluates cluster heads and best routes based on constraints.COOT outperforms other Metaheuristics Algorithms like Butterfly Optimization Algorithm, Genetic Algorithm, Tunicate Swarm Gray Wolf Optimization Algorithm, and Bird Swarm Algorithm in simulation with performance measurements and enhancing network functionality and protection.Key methodology points include: • Proposed a multiple constraints clustering and routing technique using COAto solve the most crucial issues that arise in WSNs. • Integrated an advanced fitness function that determines cluster head selection, and the routing path based on residual energy, delay, security, trust, distance, and link quality so that energy load is evenly distributed and credible data flow is maintained across the network and made Innovative and Effective Solution. • Proven Results Demonstrated superior network performance, achieving the lowest delay, highest network lifetime (3571 rounds) and enhanced security (0.8) and trust (0.6) compared to existing algorithms with less energy consumption, making it the most suitable solution for WSN performance improvement.…”
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Optimizing Gammatone Cepstral Coefficients for Gear Fault Detection by Zrar Kh Abdul, Abdulbasit K. Al-Talabani, Wisam Hazim Gwad, Entisar Alkayal, Halgurd S. Maghdid, Safar Maghdid Asaad

“…In this research, three key parameters of GTCC, namely, the number of coefficients, maximum frequency, and minimum frequency, are optimized using two metaheuristic algorithms: Fitness Dependent Optimizer (FDO) and Grey Wolf Optimization (GWO). …”
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Multi-objective quantum hybrid evolutionary algorithms for enhancing quality-of-service in internet of things by Shailendra Pratap Singh, Gyanendra Kumar, Umakant Ahirwar, Shitharth Selvarajan, Firoz Khan

“…To address these issues, we introduce a quantum-inspired hybrid algorithm that combines the strengths of Multi-Objective Grey Wolf Optimization Algorithm (MOGWOA) and Multi-Objective Whale Optimization Algorithm (MOWOA), enhanced with quantum principles. …”
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