Route Optimization for UGVs: A Systematic Analysis of Applications, Algorithms and Challenges by Dario Fernando Yépez-Ponce, William Montalvo, Ximena Alexandra Guamán-Gavilanes, Mauricio David Echeverría-Cadena

“…Heuristic algorithms, such as Humpback Whale Optimization, Firefly Search and Particle Swarm Optimization, are commonly employed to solve complex search problems. …”
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Multi-Objective Dynamic System Model for the Optimal Sizing and Real-World Simulation of Grid-Connected Hybrid Photovoltaic-Hydrogen (PV-H₂) Energy Systems by Ayatte I. Atteya, Dallia Ali, Nazmi Sellami

“…The model integrates a Particle Swarm Optimisation (PSO) algorithm that enables minimising both the levelised cost of energy (LCOE) and the building carbon footprint with a dynamic model that considers the real-world behaviour of the system components. …”
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Research on Fault Diagnosis of Traction Power Supply System Based on PSO-LSSVM by Lei ZHANG

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Prediction Model of Water Demand for Scouring Siltation in Coastal River Networks Based on APSO and SVM: A Case Study of Doulong Port by MA Zhutong, XIANG Long, YAN Ke

“…A predictive model of water demand for scouring siltation was constructed, which combined adaptive particle swarm optimization (APSO) algorithm with support vector machine (SVM) and optimized the model parameters of the SVM through the APSO algorithm, enhancing the prediction accuracy of the APSO-SVM model. …”
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Prediction Model of Water Demand for Scouring Siltation in Coastal River Networks Based on APSO and SVM: A Case Study of Doulong Port by MA Zhutong, XIANG Long, YAN Ke

“…A predictive model of water demand for scouring siltation was constructed, which combined adaptive particle swarm optimization (APSO) algorithm with support vector machine (SVM) and optimized the model parameters of the SVM through the APSO algorithm, enhancing the prediction accuracy of the APSO-SVM model. …”
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Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model by Chuansheng Zhang, Minglai Yang

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Synergistic SAPSO-sinusoidal decay empirical formula for ship motion forecasting in waves by Jianwei Wang, Xinyu Han, Jiachen Chai, Wenlei Li, Ze He, Minghua Yue

“…Recent studies have demonstrated the effectiveness of metaheuristic optimisation algorithms (e.g. Particle Swarm Optimization, PSO) in multivariate dynamic response prediction. …”
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Dynamic UAV Task Allocation and Path Planning with Energy Management Using Adaptive PSO in Rolling Horizon Framework by Zhen Han, Weian Guo

“…We introduce an enhanced Particle Swarm Optimization (PSO) algorithm, incorporating adaptive perturbation strategies and a local search mechanism based on simulated annealing, to optimize UAV task assignments and routes. …”
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Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…The model is designed to capture complex emotional nuances and themes in literature by processing text data from both forward and backward directions, while the attention mechanism enables the model to focus on the most important sections of the text. Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
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Natural gas bi-level demand response strategies considering incentives and complexities under dynamic pricing by Huibin Zeng, Jie Zhou, Hongbin Dai

“…This model is solved using multi-population ensemble particle swarm optimization (MPEPSO) and Deep Q-Network (DQN) algorithms. …”
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A comprehensive study of recent maximum power point tracking techniques for photovoltaic systems by Mohammed Hamouda Ali, Mohammad Zakaria, Sally El-Tawab

“…The perturb & observe (P&O) and incremental conductance (INC) methods have been used as conventional methods. In contrast, particle swarm optimization (PSO) has been used as a metaheuristic method. …”
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Dynamic performance improvement of oscillating water column wave energy conversion system using optimal walrus optimization algorithm-based control strategy by Habiba A. ElDemery, Hany M. Hasanien, Mohammed Alharbi, Chuanyu Sun, Dina A. Zaky

“…The proposed WOA-based PI controller design’s effectiveness is evaluated by comparing its simulation results with that obtained from using genetic algorithm (GA), grey wolf (GWO), particle swarm (PWO), and harmony search (HS) optimization-based PI controllers under symmetrical and unsymmetrical faults. …”
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LEADERS AND FOLLOWERS ALGORITHM FOR TRAVELING SALESMAN PROBLEM by Helen Yuliana Angmalisang, Syaiful Anam

“…Leaders and Followers algorithm is a metaheuristics algorithm. In solving continuous optimization, this algorithm is proved to be better than other well-known algorithms, such as Genetic Algorithm and Particle Swarm Optimization. …”
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Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems by Thang Trung Nguyen, Thai Dinh Pham, Le Chi Kien, Le Van Dai

“…Furthermore, we have also applied five other metaheuristic algorithms consisting of biogeography-based optimization (BBO), genetic algorithm (GA), particle swarm optimization algorithm (PSO), sunflower optimization (SFO), and salp swarm algorithm (SSA) for dealing with the same problem and evaluating further performance of ICOA. …”
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Application of Harris Hawks Optimization Algorithm in Optimization of Generalized Nonlinear Muskingum Parameters ——A Case Study of the Luohe River by CHEN Haitao, ZHAO Zhijie

“…The Muskingum model plays an important role in river flood simulation,and its simulation accuracy relies on the optimal selection of parameters.To address the current challenges in parameter calibration for the Muskingum model,such as complex solution processes and low accuracy,the use of the Harris Hawks optimization (HHO) algorithm was proposed to optimize its parameters.HHO algorithm has a wide range of global search capabilities,with fewer parameters to be adjusted.Taking Luohe River,a tributary of the Yellow River,as the research object,the generalized nonlinear Muskingum model was used to simulate the flood in the Yiyang-Baimasi section of the river.The parameters were optimized by employing the HHO algorithm,particle swarm optimization (PSO) algorithm,and ant colony optimization (ACO) algorithm,respectively.The results show that the generalized nonlinear Muskingum model based on the HHO algorithm achieved high simulation accuracy in the Yiyang-Baimasi section of the Luohe River,with a Min.SSD of 1 237 and the flood peak error (DPO) of only 5,outperforming those obtained through optimization using PSO algorithm and ACO algorithm.The results are suitable for application in flood forecasting in the Yiyang-Baimasi section of the Luohe River.…”
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An innovative coverage optimization method for smart information monitoring in agricultural IoT using the multi-strategy Pelican optimization algorithm by Wei Chen, Qike Cao, Bingyu Cao, Bo Jin

“…Comparative experiments with Improved Artificial Bee Colony Algorithm (IABC), Chaotic Adaptive Firefly Optimization Algorithm (CAFA), Adaptive Particle Swarm Optimization (APSO), and Lévy Flight Strategy Chaotic Snake Optimization Algorithm (LCSO) demonstrate that MSPOA improves network coverage by 5.85%, 11.33%, 21.05%, and 20.66%, respectively. …”
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A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems by Mohamed H. ElMessmary, Hatem Y. Diab, Mahmoud Abdelsalam, Mona F. Moussa

“…The proposed technique is compared with the particle swarm optimization (PSO), multi-verse optimization (MVO), grasshopper optimization (GOA), and Harris hawk optimization (HHO) and hippopotamus optimization (HO) algorithms through MATLAB simulations by applying them to the IEEE 30-bus system under various operational circumstances. …”
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Modulation optimization method for seven-level SHEPWM inverter based on EPSO algorithm by Renzheng Wang, Yuncheng Zhang, Ying Chen, Zhenyao Xin, Di Fan

“…In this paper, a modulation optimization method for seven-level SHEPWM inverter based on the Evolutionary Particle Swarm Optimization (EPSO) algorithm is proposed to address this problem, so that the algorithm quickly converges to the global optimum solution. …”
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Optimization of Planning Layout of Urban Building Based on Improved Logit and PSO Algorithms by Yun Li, Yanping Chen, Miaoxi Zhao, Xinxin Zhai

“…The particle in the particle swarm is assigned to the index parameter of logit model, and then the logit model in the evaluation system is run. …”
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Multiobjective Optimization of Irreversible Thermal Engine Using Mutable Smart Bee Algorithm by M. Gorji-Bandpy, A. Mozaffari

“…The results have been checked with some of the most common optimizing algorithms like Karaboga’s original artificial bee colony, bees algorithm (BA), improved particle swarm optimization (IPSO), Lukasik firefly algorithm (LFFA), and self-adaptive penalty function genetic algorithm (SAPF-GA). …”
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