A new intelligently optimized model reference adaptive controller using GA and WOA-based MPPT techniques for photovoltaic systems by Nassir Deghfel, Abd Essalam Badoud, Farid Merahi, Mohit Bajaj, Ievgen Zaitsev

“…The suggested controller is also optimized through two popular meta-heuristic algorithms: The genetic algorithm (GA) and the whale optimization algorithm (WOA). …”
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Efficient Pairing in Unknown Environments: Minimal Observations and TSP-Based Optimization by Naoki Fujita, Nicolas Chauvet, Andre Rohm, Ryoichi Horisaki, Aohan Li, Mikio Hasegawa, Makoto Naruse

“…We demonstrate heuristic algorithms in solving the Pairing-TSP efficiently. …”
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Optimizing Microsatellite Marker Panels for Genetic Diversity and Population Genetic Studies: An Ant Colony Algorithm Approach with Polymorphic Information Content by Ryan Rasoarahona, Pish Wattanadilokchatkun, Thitipong Panthum, Thanyapat Thong, Worapong Singchat, Syed Farhan Ahmad, Aingorn Chaiyes, Kyudong Han, Ekaphan Kraichak, Narongrit Muangmai, Akihiko Koga, Prateep Duengkae, Agostinho Antunes, Kornsorn Srikulnath

“…Optimizing reduced microsatellite panels using heuristic algorithms eases budget constraints in genetic diversity and population genetic assessments. …”
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Using Optimisation Meta-Heuristics for the Roughness Estimation Problem in River Flow Analysis by Antonio Agresta, Marco Baioletti, Chiara Biscarini, Fabio Caraffini, Alfredo Milani, Valentino Santucci

“…Five well-known meta-heuristic algorithms are employed to achieve this goal, these being a classic Evolution Strategy, a Differential Evolution algorithm, the popular Covariance Matrix Adaptation Evolution Strategy, a classic Particle Swarm Optimisation and a Bayesian Optimisation framework. …”
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Dynamic reconfiguration for TEG systems under heterogeneous temperature distribution via adaptive coordinated seeker by Yijun Chen, Bo Yang, Zhengxun Guo, Jingbo Wang, Mengmeng Zhu, Zilin Li, Tao Yu

“…In addition, an equivalent re-optimization strategy for a reconfiguration solution obtained by meta-heuristic algorithms (MhAs) is proposed to reduce redundant switching actions caused by the randomness of MhAs. …”
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Query Join Order Optimization Method Based on Dynamic Double Deep Q-Network by Lixia Ji, Runzhe Zhao, Yiping Dang, Junxiu Liu, Han Zhang

“…The performance of the proposed method is compared with those of dynamic programming, heuristic algorithms, and DRL optimization methods based on the query set Join Order Benchmark (JOB). …”
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Optimization of PID Controller to Stabilize Quadcopter Movements Using Meta-Heuristic Search Algorithms by Alaa Sheta, Malik Braik, Dheeraj Reddy Maddi, Ahmed Mahdy, Sultan Aljahdali, Hamza Turabieh

“…This study presents PID controller tuning using meta-heuristic algorithms, such as Genetic Algorithms (GAs), the Crow Search Algorithm (CSA) and Particle Swarm Optimization (PSO) to stabilize quadcopter movements. …”
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A Novel Hybrid Prairie Dog Algorithm and Harris Hawks Algorithm for Resource Allocation of Wireless Networks by Mohammad Hijjawi, Mohammad Alshinwan, Osama Ahmed Khashan, Waleed Alomoush, Nader Abdel Karim, Ahmed Younes Shdefat, Saad Said Alqahtany, Eman Shudayfat

“…For instance, no optimal performance can be guaranteed using the heuristic algorithms; besides, the global optimization systems suffer from exponential computation complexity and considerable training duration. …”
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Multicast traffic grooming in tap-and-continue WDM mesh networks by Lin, Rongping, Zhong, Wen-De, Bose, Sanjay Kumar, Zukerman, Moshe

“…Since the ILP is not scalable, two heuristic algorithms, multicast trail grooming (MTG) and multiple destination trail-based grooming (MDTG), are proposed. …”
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Great Deluge and Extended Great Deluge based job scheduling in grid computing using GridSim by Seifaddini, Omid, Abdullah, Azizol, Muhammed, Abdullah, Hussin, Masnida

“…Job scheduling in Grid computing is a NP-Complete problem due to Grid characteristics such as heterogeneity and dynamicity. Many heuristic algorithms have been proposed for Grid scheduling to avail Grid computing. …”
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Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin

“…The performance of PSO was then compared with other meta-heuristic algorithms, including Genetic Algorithm (GA) and Ant Colony Optimisation (ACO), Whale Optimisation Algorithm (WOA), Ant Lion Optimiser (ALO), Dragonfly Algorithm (DA), Grasshopper Optimisation Algorithm (GOA), Moth Flame Optimisation (MFO) and Sine Cosine Algorithm (SCA). …”
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Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

“…Moreover, the proposed FAEPO requires 50% less fitness function evaluation in each iteration than the ancestor EPO and exhibits competitive performance in terms of convergence and computational time against its predecessor (EPO) and other competing meta-heuristic algorithms with a 90% confidence level.…”
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Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

“…Performance of the QPSO technique based on many heuristic algorithms it is comprised the following steps. …”

Photovoltaic Models’ Parameter Extraction Using New Artificial Parameterless Optimization Algorithm by Mohana Alanazi, Abdulaziz Alanazi, Ahmad Almadhor, Hafiz Tayyab Rauf

“…We present the results of a comparative study using APLO and well-known existing parameter-less meta-heuristic algorithms such as grey wolf optimization, the salp swarm algorithm, JAYA, teaching-learning based optimization, colliding body optimization, as well as three major parameter-based algorithms such as differential evolution, genetic algorithm, and particle swarm optimization to estimate the parameters of PV the modules. …”
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Rapid Production Rescheduling for Flow Shop Under Machine Failure Disturbance Using Hybrid Perturbation Population Genetic Algorithm-Artificial Neural Networks (PPGA-ANNs) by Pakkaporn Saophan, Warut Pannakkong, Raveekiat Singhaphandu, Van-Nam Huynh

“…In conclusion, the proposed framework is capable of minimizing the makespan with a short computational time for real-world production, addressing the limitations of existing state-of-the-art meta-heuristic algorithms.…”
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Efficient Approach to Color Image Segmentation Based on Multilevel Thresholding Using EMO Algorithm by Considering Spatial Contextual Information by Srikanth Rangu, Rajagopal Veramalla, Surender Reddy Salkuti, Bikshalu Kalagadda

“…To study the experimental results of the proposed scheme, several color benchmark images are considered at various threshold levels and compared with other meta-heuristic algorithms: multi-verse optimization, whale optimization algorithm, and so on. …”
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A Comparative Study of Optimal PV Allocation in a Distribution Network Using Evolutionary Algorithms by Wenlei Bai, Wen Zhang, Richard Allmendinger, Innocent Enyekwe, Kwang Y. Lee

“…Optimal PV allocation (sizing and location) is challenging because it involves mixed-integer non-linear programming with three-phase non-linear unbalanced power flow equations. Meta-heuristic algorithms have proven their effectiveness in many complex engineering problems. …”
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Trust-Based Beacon Node Localization Algorithm for Underwater Networks by Exploiting Nature Inspired Meta-Heuristic Strategies by Umar Draz, Muhammad Hasanain Chaudary, Tariq Ali, Abid Sohail, Muhammad Irfan, Grzegorz Nowakowski

“…This framework helps to merge two disciplines; it is hybrid because it follows the nature and bio inspired meta heuristics algorithms for scheduling the beacon nodes. The performance of the proposed approach is also evaluated for different factors such as node losses, packet delivery ratios, residual and energy consumption and waiting time analysis, etc. …”
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Data-Driven Hyperparameter Optimized Extreme Gradient Boosting Machine Learning Model for Solar Radiation Forecasting by Kumari Namrata, Mantosh Kumar, Nishant Kumar

“…To address this critical forecasting issue in this research article a hyper parametric tuning of the Extreme Gradient Boosting (XGB) machine learning model has been carried out using two met heuristic algorithms: Moth Flame Optimization (MFO) and Grey Wolf Optimization (GWO). …”
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System Economy Improvement and Risk Shortening by Fuel Cell-UPFC Placement in a Wind-Combined System by Mitul Ranjan Chakraborty, Subhojit Dawn, Pradip Kumar Saha, Jayanta Bhusan Basu, Taha Selim Ustun

“…In the last section, heuristic algorithms, such as sequential quadratic programming (SQP), artificial bee colony algorithms (ABC), and moth-flame optimization algorithms (MFO), are employed to analyze economic risk. …”
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