HEURISTIC ALGORITHMS USAGE WHILE CONSTRUCTION OF OPTIMAL DECISION TREE FOR BUDGET MANAGEMENT by A. A. Fiodarau, S. O. Novikov

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POWER CONTROL OF PSEUDOLITES WHILE LANDING AN AIRCRAFT by V. V. Erokhin

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Optimizing performance of WPCN based on whale optimization algorithm by Lina Yuan, Huajun Chen, Tinghong Chang, Ging Gong

“…Abstract This paper investigates the optimization issues of wireless powered communication (WPC) networks and proposes a technique that is grounded in the whale optimization algorithm (WOA) to address key optimization problems such as node deployment, energy allocation, power control, and multi-user access within the network. …”
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ACCEPTABLE LIMITS FOR CORRECTION OF HEATING LOAD WHILE OPTIMIZING OPERATIONAL MODES OF HEAT SOURCES by P. I. Diachek, V. A. Sednin, A. E. Zakharevich, I. V. Shkliar

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MATHEMATICAL ASPECTS OF AIRCRAFT ENGINES RUNNING OPTIMIZATION FOR MINIMUM FUEL CONSUMPTION WHILE LANDING by Y. M. Chinyuchin, V. A. Belkin

“…The algorithm for the problem of optimal civil aircraft flight control aimed at the most accurate realization of chosen soft path under limited time conditions is proposed. …”
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Application of Improved Whale Algorithm to Optimize Dephosphorization Process Parameters in Converter Steelmaking by Congrui Wu, Yueping Kong

“…This study addresses process parameter optimization challenges in converter steelmaking by proposing an improved multi-objective whale optimization algorithm (IMOWOA) that synergistically integrates metallurgical thermodynamics with data-driven modeling. …”
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Genetic Algorithms Applied to Optimize Neural Network Training in Reference Evapotranspiration Estimation by Eluã Ramos Coutinho, Jonni G.F. Madeira, Robson Mariano da Silva, Angel Ramon Sanchez Delgado, Alvaro L.G.A. Coutinho

“…This confirms that employing Genetic Algorithms (GA) to automate the training and optimization of the model is effective and enhances the neural network's capacity to predict ETo.…”
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Optimal PID controller with evolutionary optimization algorithms for rehabilitation robots by Kamran Joyo, Talha Ahmed Khan, Kushsairy Abdul Kadir, Mohd Nizam Bin Husen, Haidawati Mohamad Nasir, Munaza Azhar

“…The Firefly algorithm also delivered promising results, achieving the shortest rise time (0.689 s) and a quick settling time (1.08 s), while keeping the overshoot (4.45%) nearly on par with PSO. …”
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Statistical Analysis Method for Optimal Prameters of Telemetry Communication by XIE Jun, WU Sailong, HAO Hang, ZHANG Songwei, WU Ruiqing, SUN Xiangyang

“…In addition, the proposed method completes a parameter optimization time of merely 0.08 seconds when processing 350 000 logging data points, demonstrating significant superiority over the existing optimization method based on machine learning and genetic algorithm. …”
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An innovative genetic algorithm-based master schedule to optimize job shop scheduling problem by Thi Phuong Quyen Nguyen, Thi Hoa Thuong Le

“…Consequently, the objective of this study is to develop an advanced method to optimize the production scheduling problem. Accordingly, this study proposes an innovative genetic algorithm-based master schedule (GA-MS) focused on minimizing makespan. …”
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Sigmoid-Function-Based Adaptive Pelican Optimization Algorithm for Global Optimization by A. F. S. Yussif, S. Adjei, B. E. Wilson

“… This paper introduces the Sigmoid-function-based Adaptive Pelican Optimization Algorithm (MPOA), an enhanced version of the traditional Pelican Optimization Algorithm (POA) aimed at improving the POA's performance. …”
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Using PSO and Genetic Algorithms to Optimize ANFIS Model for Forecasting Uganda’s Net Electricity Consumption by Kürşat Ayan, Abdal Kasule

“…We use particle swarm optimization (PSO) algorithm and genetic algorithm (GA) to optimize the parameters of the model. …”
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SOMO-m Optimization Algorithm with Multiple Winners by Wei Wu, Atlas Khan

“…More importantly, SOMO-m algorithm with m≥2 can be used to find two or more minimums simultaneously in a single learning iteration process, while the original SOM-based optimization (SOMO) algorithm has to fulfil the same task much less efficiently by restarting the learning iteration process twice or more times.…”
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An Optimized Strategy Coverage Control Algorithm for WSN by Zeyu Sun, Weiguo Wu, Huanzhao Wang, Heng Chen, Wei Wei

“…Thirdly, OSCC picks out the optimal routing solution while conducting combinatorial optimization of routing path using ant colony optimization (ACO) algorithm, thus reducing the energy spending of whole network. …”
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Metaheuristic Algorithms for Optimization: A Brief Review by Vinita Tomar, Mamta Bansal, Pooja Singh

“…In the area of optimization, metaheuristic algorithms have attracted a lot of interest. …”
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ＲGB-DSLAM Visual Odometry Optimization Algorithm by DONG Jing-wei, JIANG Yi-ming, HAN Zhi-yu

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NETWORK MODEL AND ALGORITHM FOR SOLVING PROBLEM PERTAINING TO OPTIMUM DISTRIBUTION OF CAPITAL INVESTMENT WHILE MODERNIZING ENTERPRISES OF HEATING SYSTEMS by V. A. Sednin, A. D. Korznikov, А. V. Sednin

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Hierarchical multi step Gray Wolf optimization algorithm for energy systems optimization by Idriss Dagal, AL-Wesabi Ibrahim, Ambe Harrison, Wulfran Fendzi Mbasso, Ahmad O. Hourani, Ievgen Zaitsev

“…Abstract Gray Wolf Optimization (GWO), inspired by the social hierarchy and cooperative hunting behavior of gray wolves, is a widely used metaheuristic algorithm for solving complex optimization problems in various domains, including engineering design, image processing, and machine learning. …”
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Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …”
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