A Multi-Objective Optimization Design Method for High-Aspect-Ratio Wing Structures Based on Mind Evolution Algorithm Backpropagation Surrogate Model by Jin Nan, Junhua Zheng, Bochuan Jiang, Yuhang Li, Jiayun Chen, Xuanqing Fan

“…The wing structure optimization model was established using the multi-objective grey wolf optimizer (MOGWO) based on the surrogate model for search and optimization. …”
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Optimal rule-based energy management and sizing of a grid-connected renewable energy microgrid with hybrid storage using Levy Flight Algorithm by Babangida Modu, Md Pauzi Abdullah, Abdulrahman Alkassem, Mukhtar Fatihu Hamza

“…The result demonstrate that the LFA outperforms methods like the Salp Swarm Algorithm (SSA), Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Genetic Algorithm (GA), yielding cost savings of $3,309, $5,297, $4,484, and $5,129 respectively. …”
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A Meta-Heuristic Algorithm-Based Feature Selection Approach to Improve Prediction Success for Salmonella Occurrence in Agricultural Waters by Murat Canayaz, Murat Demir, Zeynal Topalcengiz

“…Features were selected by using binary meta-heuristic optimization methods including differential evolution optimization (DEO), grey wolf optimization (GWO), Harris hawks optimization (HHO) and particle swarm optimization (PSO). …”
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A Two-Stage Optimization Framework for UAV Fleet Sizing and Task Allocation in Emergency Logistics Using the GWO and CBBA by Yongchao Zhang, Wei Xu, Helin Ye, Zhuoyong Shi

“…To address this gap, this paper proposes a novel two-stage hierarchical framework that integrates the Grey Wolf Optimizer (GWO) with the Consensus-Based Bundle Algorithm (CBBA). …”
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Hermetically sealed ecodesign distribution transformer weight optimization considering power losses and total ownership cost (TOC) by Mohammad Hassan Hashemi, Ulas Kilic

“…Specifically, the study employs Differential Evolution (DE), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) algorithms to compare their efficacy against conventional design approaches. …”
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Orthogonal Multi‐Swarm Greedy Selection Based Sine Cosine Algorithm for Optimal FACTS Placement in Uncertain Wind Integrated Scenario Based Power Systems by Sunilkumar P. Agrawal, Pradeep Jangir, Arpita, Sundaram B. Pandya, Anil Parmar, Mohammad Khishe, Bhargavi Indrajit Trivedi

“…Flexible AC Transmission System (FACTS) devices, including Static VAR Compensator (SVC), Thyristor‐Controlled Series Compensator (TCSC), and Thyristor‐Controlled Phase Shifter (TCPS), enhance system stability, reduce losses, and lower operational costs when optimally placed. Conventional optimization techniques like Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Moth Flame Optimization (MFO), Gray Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) struggle to balance exploration and exploitation in complex OPF problems, leading to suboptimal solutions. …”
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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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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

“…ABSTRACT As renewable energy sources (RES) are increasingly unified into multiarea power systems, automatic generation control (AGC) faces challenges such as frequency instability, longer settling times, and higher overshoot. While existing optimization techniques like Firefly (FF) and gray wolf (GW) suffer from slow convergence and local optima trapping, conventional controllers like FOPI, PIDN, TIDN, and TIDDN struggle to maintain stability under fluctuating load conditions. …”
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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 Load Frequency Control of Multi-Area Power Renewable and Thermal Systems Using Advanced Proportional–Integral–Derivative Controllers and Catch Fish Algorithm by Saleh A. Alnefaie, Abdulaziz Alkuhayli, Abdullah M. Al-Shaalan

“…The performance of LFC with CFA-tuned PID, PI, cascaded PI(PDN), and FOPID, PI(1+DD) controllers is compared to other optimization techniques, including sine cosine algorithm (SCA), particle swarm optimization (PSO), brown bear algorithm (BBA), and grey wolf optimization (GWO), in a two-area power system combined with RESs under various conditions. …”
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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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Modeling and optimization of an M/M/1/K queue with single working vacation, feedback, and impatience timers under N-policy by Abir Kadi, Mohamed Boualem, Nassim Touche, Aimen Dehimi

“…After constructing the expected cost function of the model, Grey Wolf Optimization (GWO) algorithm is utilized to determine the optimum values of the service rates \(\mu^{*}\) and \(\mu_{v}^{*}\). …”
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Enhanced Multi-Threshold Otsu Algorithm for Corn Seedling Band Centerline Extraction in Straw Row Grouping by Yuanyuan Liu, Yuxin Du, Kaipeng Zhang, Hong Yan, Zhiguo Wu, Jiaxin Zhang, Xin Tong, Junhui Chen, Fuxuan Li, Mengqi Liu, Yueyong Wang, Jun Wang

“…The experimental results show that SADE-WOA accurately separates soil regions while preserving straw texture, achieving higher between-class variance and significantly faster convergence than the other tested algorithms. It runs at just one-tenth of the time of the Grey Wolf Optimizer and one-ninth of that of DE and requires only one-sixth to one-seventh of the time needed by DE-GWO. …”
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Multi robot exploration using an advanced multi-objective salp swarm algorithm for efficient coverage and performance by Ali El Romeh, Seyedali Mirjalili

“…To validate its effectiveness, AMET is compared to both multi-objective and single-objective exploration strategies, including CME combined with Multi-Objective Grey Wolf Optimizer (CME-MGWO), Multi-Objective Ant Colony Optimization (CME-MACO), Multi-Objective Dragonfly Algorithm (CME-MODA), and the single-objective CME with traditional Salp Swarm Algorithm (CME-SSA). …”
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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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Optimal Allocation and Sizing of Multiple DGs with Reactive Power Capabilities in a Three-Phase Unbalanced Distribution System by Zahıra Aboumarıa, Selcuk Emiroglu

“…The DG size, node, and power factor are the coordinated control variables presented in this study to minimize the power loss. Genetic Algorithm, Pattern Search, Particle Swarm Optimization, and Grey Wolf Optimizer algorithms have been exploited in the IEEE 37 node test feeder to find the optimal location, sizes, and power factors of the DGs. …”
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Optimizing Cold Chain Logistics with Artificial Intelligence of Things (AIoT): A Model for Reducing Operational and Transportation Costs by Hamed Nozari, Maryam Rahmaty, Parvaneh Zeraati Foukolaei, Hossien Movahed, Mahmonir Bayanati

“…This study considers equipping distribution centers and trucks with IoT tools and examines the advantages of using these tools to reduce logistics costs. Also, four algorithms based on artificial intelligence (AI), including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gray Wolf Optimizer (GWO), and Emperor Penguin Optimizer (EPO), have been used in solving the mathematical model. …”
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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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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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A novel global MPPT method based on sooty tern optimization for photovoltaic systems under complex partial shading by Mohammed Taha Kaaitan, Rashid Ali Fayadh, Zuhair S. AL-sagar, Salam J. Yaqoob, Mohit Bajaj, Mebratu Sintie Geremew

“…Performance evaluation against benchmark algorithms—Perturb & Observe (P&O), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO)—revealed that STOA consistently outperformed its counterparts. …”
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