A Scalable Ensemble Learning-Based Model for Optimal Placement of Circuit Breaker and Sectionalizer in Power Distribution Systems with the Aim of Reliability Improvement by Mehrdad Ebrahimi, Mohammad Rastegar

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Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm by ARIYO Funso Kehinde, AYANLADE Samson Oladayo, JIMOH Abdulrasaq, ADEBAYO Moses Taiwo

“…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
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Application of Optimization Algorithms in Voter Service Module Allocation by Edgar Jardón, Marcelo Romero, José-Raymundo Marcial-Romero

“…Six heuristics were analyzed in sequence: genetic algorithm, ant colony optimization, local search, tabu search, simulated annealing, and greedy algorithm. …”
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Optimized multi-unit coordinated scheduling based on improved IGDT: Low-carbon scheduling research for the electric-heat-oxygen integrated energy system by Zhe Yin, Zhifan Zhang, Ruijin Zhu, Yifan Zhang, Jiyuan Wang, Wenxing Tang

“…This model combines the entropy weight method (EWM) and non-dominated sorting genetic algorithm II (NSGA-II), improving the objectivity and rationality of uncertainty weight settings in risk-averse strategy (RAS) and risk-seeking strategy (RSS). …”
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A Projection Strategy for Improving the Preconditioner in the LOBPCG by Ma Tailai, Sun Shuli, Zheng Fangyi, Chen Pu

“…This oblique projection technique can find a more accurate approximate solution which minimizes the 2-norm residuals in the search subspace without significantly increasing computational cost, thereby improving the quality of the preconditioner, thus accelerating convergence of the LOBPCG.Numerical experiments show that the projection strategy can improve the LOBPCG algorithm significantly in terms of efficiency and stability.…”
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ANFIS-optimized control for resilient and efficient supply chain performance in smart manufacturing by Mona A. AbouElaz, Bilal Naji Alhasnawi, Bishoy E. Sedhom, Vladimír Bureš

“…This paper evaluates the supply chain (SC) using the adaptive neuro-fuzzy inference system (ANFIS) classification control algorithm to improve the SC performance, maximize the system quality, and minimize the cost. …”
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An optimal design method of the resonant-free C-type filter by XU Fangwei, JIA Junwei, GUO Kai, XU Lin, CHEN Jiale, LU Yuguo

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Low-carbon economic optimization for flexible DC distribution networks based on the hiking optimization algorithm by Ke Wu, Yuefa Guo, Ke Wang, Zhenliang Chen

“…This leads to improved optimization accuracy, further validating its effectiveness in IES optimization.…”
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Multi-Timescale Battery-Charging Optimization for Electric Heavy-Duty Truck Battery-Swapping Stations, Considering Source–Load–Storage Uncertainty by Peijun Shi, Guojian Ni, Rifeng Jin, Haibo Wang, Jinsong Wang, Zhongwei Sun, Guizhi Qiu

“…We propose a day-ahead charging strategy optimization algorithm based on intra-day optimization feedback information-gap decision theory (IGDT) and an improved grasshopper algorithm for intra-day charging strategy optimization. …”
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Reliability Analysis of High-Pressure Tunnel System Under Multiple Failure Modes Based on Improved Sparrow Search Algorithm–Kriging–Monte Carlo Simulation Method by Yingdong Wang, Chen Xing, Leihua Yao

“…Then, the improved sparrow search algorithm (ISSA) is used to optimize the hyper-parameters of the Kriging surrogate model, in order to improve the computational efficiency and accuracy of the reliability analysis model. …”
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A new sliding mode control strategy to improve active power management in a laboratory scale microgrid by Oscar Gonzales-Zurita, Jean-Michel Clairand, Guillermo Escrivá-Escrivá

“…This study proposes a robust control solution based on the second-order sliding mode control (SMC-2) algorithm to overcome the mentioned challenges. This algorithm employed a non-conventional sliding surface to improve the microgrid’s capacities for energy management. …”
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Three Strategies Enhance the Bionic Coati Optimization Algorithm for Global Optimization and Feature Selection Problems by Qingzheng Cao, Shuqi Yuan, Yi Fang

“…However, raw training datasets often contain abundant redundant features, which increase model training’s computational cost and impair generalization ability. To tackle this, this study proposes the bionic ABCCOA algorithm, an enhanced version of the bionic Coati Optimization Algorithm (COA), to improve redundant feature elimination in datasets. …”
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A Gradient-Based Optimization Algorithm for Optimal Control Problems With General Conformable Fractional Derivatives by Essia Ben Alaia, Slim Dhahri, Omar Naifar

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Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…This paper proposes a cooperative sleep and energy-sharing strategy for heterogeneous 5G base station microgrid (BSMG) systems, utilizing deep learning and an improved multi-objective evolutionary algorithm based on decomposition (MOEA/D). …”
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Renewable energy forecasting using optimized quantum temporal model based on Ninja optimization algorithm by Mona Ahmed Yassen, El-Sayed M. El-kenawy, Mohamed Gamal Abdel-Fattah, Islam Ismael, Hossam El.Deen Salah Mostafa

“…Abstract Artificial intelligence allows improvements in renewable energy systems by increasing efficiency while enhancing reliability and reducing costs. …”
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Impact of Network Configuration on Hydraulic Constraints and Cost in the Optimization of Water Distribution Networks by Mojtaba Nedaei

“…Further, a new approach based on the Coral Reef Algorithm (CRA) is developed and implemented to improve the technical and economic viability of the designed WDNs. …”
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Offshore Wind Farm Layout Optimization Considering the Power Collection System Cost by S. G. Obukhov, D. Y. Davydov

“…The change in the size and shape of the boundaries of the wind farm site resulted in an increase in the estimated electricity generation by 2.3 % and a decrease in its cost by 4 %. When optimizing the layout of wind turbines within the fixed boundaries of the site, these indicators are improved by only 1 and 2 % as compared to the original scheme.…”
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Well Pattern optimization as a planning process using a novel developed optimization algorithm by Seyed Hayan Zaheri, Mahdi Hosseini, Mohammad Fathinasab

“…The novelty of this work is the integrated algorithm, which improves searching performance by leveraging the memorizing characteristics of the particle swarm optimization algorithm to enhance genetic algorithm efficiency. …”
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Multi strategy Horned Lizard Optimization Algorithm for complex optimization and advanced feature selection problems by Marwa M. Emam, Mosa E. Hosney, Reham R. Mostafa, Essam H. Houssein

“…However, when applied to high-dimensional datasets characterized by a vast number of features and limited samples-these methods often suffer from performance degradation and increased computational costs. The Horned Lizard Optimization Algorithm (HLOA) is a nature-inspired metaheuristic that mathematically mimics the adaptive defense mechanisms of horned lizards, including crypsis, skin color modulation, blood-squirting, and escape movements. …”
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Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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