Uncertainty-aware multi-objective growth optimizer of EV charging stations allocation in unbalanced grids by Abdullah M. Shaheen, Aya R. Ellien, Adel A. El-Ela, Ali M. El-Rifaie

“…Benchmark comparisons with established metaheuristic algorithms of Particle Swarm Optimization (PSO), the original GO, and the Enzyme Action Optimizer (EAO) highlight AMOGO’s superior performance. …”
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Sistem Kontrol Swarm untuk Flocking Wahana NR-Awak Quadrotor dengan Optimasi Algoritma Genetik by Endra Joelianto, Winarendra Satya Rajasa, Agus Samsi

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Optimizing Multi-Quay Combined Berth and Quay Crane Allocation Using Computational Intelligence by Sheraz Aslam, Michalis P. Michaelides, Herodotos Herodotou

“…For comparison purposes, we implement two baseline approaches, first come first serve and exact MILP, and two CI approaches, particle swarm optimization (PSO) and genetic algorithm (GA), that are typically used to solve such complex or NP-hard problems. …”
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Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm by Xiang Wu, Zhen Yang, Dongdong Wu

“…Despite these progresses, predicting the gas outburst more accurately and efficiently still remains a great challenge. In this work, an algorithm based on grey relational analysis and SVM using adaptive particle swarm optimization (APSO-SVM) for gas outburst prediction is proposed. …”
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Hybrid Metaheuristic Optimization of HVAC Energy Consumption and Thermal Comfort in an Office Building Using EnergyPlus by Reza Akraminejad, Tianyi Zhao, Yacine Rezgui, Ali Ghoroghi, Yousef Shahbazi Razlighi

“…Subsequently, we employ EnergyPlus simulations, utilizing a single-objective Particle Swarm Optimization (PSO) for initial parameter analysis to generate a dataset. …”
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Symmetric Cryptography With Shift 2^n-1, Hash Transformation, Optimization-Based Controller for Medical Image Infosecurity: Case Study in Mammographic Image by Pi-Yun Chen, Jian-Xing Wu, Chien-Ming Li, Chao-Lin Kuo, Neng-Sheng Pai, Chia-Hung Lin

“…Then, swarm optimization-based controllers, which are based on particle swarm optimization (PSO) and firefly algorithm (FA), are implemented to search the decryption key parameters. …”
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Integrated decision support system for optimizing time and cost trade offs in linear repetitive construction projects by Ahmed Gouda Mohamed, Ali Hassan Ali, Ahmed Adel Abdelhady

“…Unlike previous studies that focus solely on single-algorithm applications, this research evaluates two metaheuristic optimization strategies—Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)—within a consistent problem setting. …”
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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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Configuration optimization for offset strip plate-fin heat exchanger using a method of PID-based search algorithm driving design indicators mathematical model by Zhe Xu, Zongling Yu, Xin Ning, Changyin Zhao, Fuquan Nie

“…Compared to GOOSE algorithm, Invasive Weed Optimization, and Particle Swarm Optimization, PSA achieves the high convergence efficiency and the adequate ability to escape local optima both, and performs the best with the highest computational efficiency among them. …”
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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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Optimized hybrid osprey with PSO control for improved VSC-HVDC-wind power integration by Abdulaziz Alkuhayli, Hany M. Hasanien

“…The purpose of this study is to combine the Osprey Optimization with Particle Swarm Optimization (OOPSO) to fine-tune the gains of Proportional-Integral (PI) controllers within the investigated wind energy conversion system (WECS) to enhance its performance. …”
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Fractional-Order Predictive Functional Control of Industrial Processes with Partial Actuator Failures by Min-Ying Li, Kang-Di Lu, Yu-Xing Dai, Guo-Qiang Zeng

“…The comprehensive simulation results demonstrate the performance of the proposed control method by comparing with a recently developed predictive functional control, genetic algorithm, and particle swarm optimization-based versions in terms of four performance indices.…”
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Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS-Based Cosimulation and a Proposed Metaheuristic Al... by Thai Dinh Pham, Thang Trung Nguyen, Le Chi Kien

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Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

“…To predict the VIV performance of a double-deck steel truss (DDST) girder with additional aerodynamic measures, the VIV response of a DDST bridge was investigated using wind tunnel tests and numerical simulation, a learning sample database was established with numerical simulation results, and a prediction model for the amplitude of the DDST girder and VIV parameters was established based on three machine learning algorithms. The optimization algorithm was selected using root mean square error (RMSE) and the coefficient of determination (R²) as evaluation indices and further improved with a genetic algorithm and particle swarm optimization. …”
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SASDL and RBATQ: Sparse Autoencoder With Swarm Based Deep Learning and Reinforcement Based Q-Learning for EEG Classification by Sunil Kumar Prabhakar, Seong-Whan Lee

“…Therefore, taking advantage of these factors, the first method proposed is a Sparse Autoencoder (SAE) with swarm based deep learning method and it is named as (SASDL) using Particle Swarm Optimization (PSO) technique, Cuckoo Search Optimization (CSO) technique and Bat Algorithm (BA) technique; and the second technique proposed is the Reinforcement Learning based on Bidirectional Long-Short Term Memory (BiLSTM), Attention Mechanism, Tree LSTM and Q learning, and it is named as (RBATQ) technique. …”
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Data Allocation in Distributed Database based on CSO by Saadi Hamad Thalij

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Optimum Design of a Photovoltaic Inverter System Based on Ga, Pso and Gwo Algorithms with a Mppt Sliding Mode Control by Alberto Coronado-Mendoza, Mónica Camas-Náfate, Jesús Sergio Artal-Sevil, José Antonio Domínguez-Navarro

“…Furthermore, eight system parameters are optimized using advanced techniques such as genetic algorithms, particle swarm optimization, and gray wolf optimization. …”
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Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

“…AFBO is evaluated using real-world trace-driven simulations and compared against benchmark multi-objective algorithms, including multi-objective particle swarm optimization (MOPSO), simulated annealing-based bi-objective differential evolution (SBDE), and the baseline Multi-Objective Firefly Algorithm (MOFA). …”
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Charge and discharge scheduling method for large-scale electric vehicles in V2G mode via MLGCSO by Songling Pang, Kaidi Fan, Meiyi Huo

“…Based on this model, a multi-level grouping based competitive swarm optimizer (MLGCSO) is put forward. Compared with traditional methods, the diversity and convergence of particle swarm learning are enhanced, and the optimization performance is improved. …”
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A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing by Yacine Bourek, El Mouatez Billah Messini, Chouaib Ammari, Mohamed Guenoune, Boulerbah Chabira, Bipul Krishna Saha

“…A particle swarm optimization (PSO) approach was also implemented for comparison, highlighting the advantages of the GA in terms of cost distribution and system reliability. …”
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