A Metaheuristic Framework for Cost-Effective Renewable Energy Planning: Integrating Green Bonds and Fiscal Incentives by Juan D. Saldarriaga-Loaiza, Johnatan M. Rodríguez-Serna, Jesús M. López-Lezama, Nicolás Muñoz-Galeano, Sergio D. Saldarriaga-Zuluaga

“…To do this, we use three optimization techniques to identify solutions that lower electricity generation costs: Teaching Learning, Harmony Search, and the Shuffled Frog Leaping Algorithm. …”
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A Novel Fault Diagnosis Method for Rolling Bearing Based on Improved Sparse Regularization via Convex Optimization by Dongjie Zhong, Cancan Yi, Han Xiao, Houzhuang Zhang, Anding Wu

“…To handle this difficulty, a novel fault signal denoising scheme based on improved sparse regularization via convex optimization is proposed to extract the fault feature of rolling bearing. …”
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Energy-environment-economic study and optimization: An advanced heat recovery method for improving gas turbine cycle efficiency by Chaoxin Ji, Azher M. Abed, Xiao Zhou, Guoliang Lei, Li He, T.H. AlAbdulaal, Barno Abdullaeva, Mohammad Sediq Safi

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An improved hybrid artificial bee colony algorithm for a multi-supplier closed-loop location inventory problem with customer returns. by Hao Guo, Xiaomei Lai, Ju Guo, Ge You, Ibrahim Alnafrah

“…The objective of the CLLIP is to minimize overall supply chain costs by optimizing facility location and inventory management strategies. …”
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Optimal Distributed Dispatch of Smart Multi-Agent Energy Hubs Based on Consensus Algorithm Considering Lossy Communication Network and Uncertainty by Abdelfattah A. Eladl, Magda I. El-Afifi, Magdi M. El-Saadawi, Bishoy E. Sedhom

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Construction of Prioritized T-Way Test Suite Using Bi-Objective Dragonfly Algorithm by Mashuk Ahmed, Abdullah B. Nasser, Kamal Z. Zamli

“…In software testing, effective test case generation is essential as an alternative to exhaustive testing. For improving the software testing technology, the t-way testing technique combined with metaheuristic algorithm has been great to analyze a large number of combinations for getting optimal solutions. …”
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Optimizing Equivalent Property-Damage-Only (EPDO) Prediction Models with Genetic Algorithms: A Case Study on Roundabout Geometric Characteristics by Hossein Samadi, Omid Rahmani, Khaled Shaaban, Amir Saman Abdollahzadeh Nasiri, Mehrzad Hasanvand

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Presenting a Prediction Model for CEO Compensation Sensitivity using Meta-heuristic Algorithms (Genetics and Particle Swarm) by Saeed Khaljastani, Habib Piri, Reza Sotoudeh

“…Given these points, the aim of this research is to provide a model for predicting the sensitivity of CEO compensation using meta-heuristic algorithms, specifically genetic algorithms and particle swarm optimization. …”
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Simultaneous Optimal Network Reconfiguration, DG and Fixed/Switched Capacitor Banks Placement in Distribution Systems using Dedicated Genetic Algorithm by Davar Esmaeili, Kazem Zare, Behnam Mohammadi-ivatloo, Sayyad Nojavan

“…As well, integration of distributed generation (DG) units and fixed/switched capacitor banks are effective options for operation cost reduction, reducing system losses, improving voltage profile and increasing voltage stability index in the distribution systems. …”
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Real-Time Optimal Control Strategy for Multienergy Complementary Microgrid System Based on Double-Layer Nondominated Sorting Genetic Algorithm by Min Mou, Yuhao Zhou, Wenguang Zheng, Zhongping Zhang, Da Lin, Dongdong Ke

“…This model combines with the operation control strategy suitable for multienergy complementary microgrid system, considers the operation mode and equipment characteristics of the system, and uses a double-layer nondominated sorting genetic algorithm to optimize the operation of each equipment in the multienergy complementary system in real time, so as to reduce the operation cost of the system.…”
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Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray. by Nadim Rana, Yahaya Coulibaly, Ayman Noor, Talal H Noor, Md Imran Alam, Zeba Khan, Ali Tahir, Mohammad Zubair Khan

“…To further improve feature selection, we utilize the Chaotic Whale Optimization (ChWO) Algorithm, which optimally selects the most relevant attributes from the extracted features. …”
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Exploring the effectiveness of adaptive randomized sine cosine algorithm in wind integrated scenario based power system optimization with FACTS devices by Sunilkumar P. Agrawal, Pradeep Jangir, Arpita, Sundaram B. Pandya, Anil Parmar, Ahmad O. Hourani, Bhargavi Indrajit Trivedi, Mohammad Khishe

“…The results of these experiments show faster convergence and consistent solution accuracy compared to benchmark algorithms such as Sine Cosine Algorithm (SCA), Improved Grey Wolf Optimization (IGWO), Whale Optimization Algorithm (WOA), and others. …”
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Optimization of Multi-Energy Grid Integration and Energy Storage in Low-Carbon Power Systems Based on the TCM-MBZOA Algorithm: A Case Study of Yunnan Province by Yang Li, Guoen Zhou, Jiaqi Xue, Junwei Yang, Shi Yin

“…To address this limitation, this paper proposes a multi-source coordinated optimization strategy based on a bi-level programming model and an improved tent chaotic mapping-memory backtracking zebra optimization algorithm (TCM-MBZOA). …”
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Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms by H. Feza Carlak, Ergin Kayar

“…The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. …”
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Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm by M. H. Zhang, X. Feng, M. Bano, C. Liu, Q. Liu, X. Wang

“…Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. …”
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A Bi-Objective Model for the Location and Optimization Configuration of Kitchen Waste Transfer Stations by Ming Wan, Ting Qu, George Q. Huang, Ruoheng Chen, Manna Huang, Yanghua Pan, Duxian Nie, Junrong Chen

“…An improved non-dominated sorting genetic algorithm with an elite strategy (NSGA-II) is used to solve the problem, resulting in a Pareto-optimal solution set that includes several non-dominated solutions, thereby providing diversified choices for decision-makers. …”
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Assessment of energy management and power quality improvement of hydrogen based microgrid system through novel PSO-MWWO technique by Hafiz Ghulam Murtza Qamar, Xiaoqiang Guo, Ehab Seif Ghith, Mehdi Tlija, Abubakar Siddique

“…The achieved results and numerical analysis affirm the superiority of the proposed technique compared to other traditional methods like mixed integer linear programming (MILP), HOMER, Variable mesh optimization (VMO), and Cataclysmic genetic algorithm in optimizing component sizing, renewable production, hydrogen production, reliability, cost effective, and overall efficacy. …”
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Optimum design of double tuned mass dampers using multiple metaheuristic multi-objective optimization algorithms under seismic excitation by Fateme Zamani, Sayyed Hadi Alavi, Mohammadreza Mashayekhi, Ehsan Noroozinejad Farsangi, Ataallah Sadeghi-Movahhed, Ali Majdi

“…The tuning process is carried out using a combination of Pareto front derived from seven multi-objective metaheuristic optimization algorithms with two objectives. The proposed methodology is applied to a 10-floor case study, using ground acceleration time histories to evaluate its seismic performance. …”
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A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters by Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu

“…Our results indicate that this framework achieves competitive accuracy compared to conventional random search and Bayesian optimization methods. The most significant enhancement was observed in the lattice-physics dataset, achieving a 56.6% improvement in prediction accuracy, compared to improvements of 53.2% by Hyp-RL, 44.9% by Bayesian optimization, and 38.8% by random search relative to the nominal prediction. …”
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Mexican axolotl optimization algorithm with a recalling enhanced recurrent neural network for modular multilevel inverter fed photovoltaic system by R. Madavan, B. Karthikeyan, R. Palanisamy, Mohammad Imtiyaz Gulbarga, Mohammed Al Awadh, Liew Tze Hui

“…The proposed MAO-RERNN control method integrates the Mexican Axolotl Optimization (MAO) algorithm with a Recalling-Enhanced Recurrent Neural Network (RERNN) to achieve optimal power conversion, improved stability, and reduced total harmonic distortion (THD). …”
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