An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young’s double-slit experiment algorithm by Basma S. Alqadi, Deema Mohammed Alsekait, Mohamed F. Issa, Essam H. Houssein, Fatma H. Ismail, Mokhtar Said, Nour Mostafa, Fahmi Elsayed

“…Abstract This paper introduces a novel optimization algorithm, Young’s double-slit experiment algorithm (YSDE), for accurately estimating the unknown parameters of Proton Exchange Membrane Fuel Cell (PEMFC) models. …”
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Nonlinear Hysteresis Parameter Identification of Piezoelectric Actuators Using an Improved Gray Wolf Optimizer with Logistic Chaos Initialization and a Levy Flight Variant by Yonggang Yan, Kangqiao Duan, Jianjun Cui, Shiwei Guo, Can Cui, Yongsheng Zhou, Junjie Huang, Geng Wang, Dengpan Zhang, Fumin Zhang

“…This paper proposes an improved Gray Wolf Optimization (GWO) algorithm for high-accuracy identification of hysteresis model parameters based on the Bouc–Wen (BW) differential equation. …”
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Unraveling regional variability in Dengue outbreaks in Brazil: leveraging the Moving Epidemics Method (MEM) and climate data to optimize vector control strategies. by Ayrton Sena Gouveia, Marcelo Ferreira da Costa Gomes, Iasmim Ferreira de Almeida, Raquel Martins Lana, Leonardo Soares Bastos, Lucas Monteiro Bianchi, Sara de Souza Oliveira, Eduardo Correa Araujo, Danielle Andreza da Cruz Ferreira, Dalila Machado Botelho Oliveira, Vinicius Barbosa Godinho, Luã Bida Vacaro, Thais Irene Souza Riback, Oswaldo Gonçalves Cruz, Flávio Codeço Coelho, Cláudia Torres Codeço

“…This study aimed to characterize Brazilian territory based on epidemiological and climate data to determine the optimal time to guide preventive and control strategies. …”
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A multi-faceted review of wind turbine optimization techniques: Metaheuristics and related issues by Hegazy Rezk, Abdul Ghani Olabi, Tabbi Wilberforce, Enas Taha Sayed

“…This article comprehensively reviews the current optimization state for wind energy systems and examines the use of metaheuristic optimization algorithms. …”
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O2O-PLB: A One-to-One-Based Optimizer With Priority and Load Balancing Mechanism for Resource Allocation in Fog-Cloud Environments by V. C. Bharathi, S. Syed Abuthahir, Monelli Ayyavaraiah, G. Arunkumar, Usama Abdurrahman, Sardar Asad Ali Biabani

“…However, the challenge of optimizing resource allocation remains significant, especially in dynamic and diverse environments. …”
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Fault Diagnosis System of Induction Motors Based on Neural Network and Genetic Algorithm Using Stator Current Signals by Tian Han, Bo-Suk Yang, Won-Ho Choi, Jae-Sik Kim

“…GA is used to select the most significant features from the whole feature database and optimize the ANN structure parameter. …”
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Efficient Technique for Joint Parameter Estimation of Mixed Far Field Targets and Near Field Jammers in Phased Array Radar by Fawad Zaman, Sadiq Akbar, Zohaib Akhtar, Gridsada Phanomchoeng

“…A novel approach based on the Gradient Based Optimizer (GBO) algorithm and Marine Predators Algorithm (MPA) is proposed to estimate jointly the unknown parameters related to the far field targets and near field jammers. …”
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A Transfer Matrix Norm-Based Framework for Multimaterial Topology Optimization: Methodology and MATLAB Implementation by Giacomo Galuppini, Paolo Venini

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Smart Microgrid Management and Optimization: A Systematic Review Towards the Proposal of Smart Management Models by Paul Arévalo, Dario Benavides, Danny Ochoa-Correa, Alberto Ríos, David Torres, Carlos W. Villanueva-Machado

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Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system by Qianwen LI, Jianfeng CHEN, Miao CUI, Guangchi ZHANG

“…A rechargeable unmanned aerial vehicle (UAV) aided wireless sensor network was considered, which consists of multiple ground terminals with a large amount of time-sensitive data to be collected.Due to the limited battery capacity, the UAV cannot collect the data from all terminals through a single flight mission, and it needs to return to the charging pile to replenish its flight energy several times during the whole mission.The optimization of the terminal scheduling, trajectory, flight speed and transmission rate for the UAV was studied to maximize the number of terminals whose data had been collected within the data lifetime limit.Due to the variable coupling and the existence of discrete binary scheduling variables, the considered optimization problem is difficult to solve.To tackle such a difficulty, an efficient algorithm was proposed based on the stochastic optimization and the feature engineering.Specifically, the flight hover communication protocol was introduced to simplify the UAV flight process.And then a terminal scheduling algorithm was innovatively proposed with the influence factor and the stochastic preference, which extracted the features that affect the service time of the UAV, optimized the weights of the features, and further simplified the optimization problem into multiple subproblems.The subproblems were then solved by using the block coordinate descent and successive convex approximation techniques.Simulation results show that the proposed optimization algorithm achieves significant performance gains over several benchmark schemes in the scenarios with different data lifetime requirements and different numbers of ground terminals.…”
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Enhancing sustainable urban design using machine learning: comparative analysis of seven metaheuristic algorithms in energy-efficient digital architecture by Mazin Arabasy, Rehab Salaheldin Ghoneim

“…Metaheuristics optimization algorithms used in this research include PSO, ACO, GA, and SA and represent effective approaches toward reaching an optimal or near-optimal solution for decision variables with an intention to improve energy efficiency, increasing indoor comfort whilst reducing the carbon footprint of building operations. …”
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An Improved Constrained Multiobjective Optimization for Energy Multimodal Transport Among Clustering Islands by Xu Yang, Fuxing Zhang, Honglei Miao

“…To this end, this study proposes a novel energy optimization framework that aims to optimize the use of their different types of energy among clustering islands and improve the stability of the whole energy internet via a multilayer transportation network. …”
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Evolutionary Synthesis of High-Capacity Reconfigurable Multilayer Road Networks Using a Multiagent Hybrid Clustering-Assisted Genetic Algorithm by Andranik S. Akopov, Levon A. Beklaryan

“…Therefore, it is essential to find a balance when choosing the optimal topological solution for an RMRN. These solutions need to maximize traffic flow while minimizing the complexity of the RMRN. …”
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Optimization of multi-structural parameters in metamaterials based on the DGN co-simulation method. by Shangyang Jin, Fuxing Chen, Jie Bai, Bingfei Liu

“…Then the global algorithm is combined with the local algorithm to solve the problem of poor convergence of the global optimization algorithm while ensuring the optimization quality of the local optimization algorithm. …”
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A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…Experimental findings indicate that the P-BTLBO algorithm surpasses conventional optimization methods, including TLBO and PSO, regarding classification accuracy, feature subset size, and computational efficiency. …”
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Optimized Integral Super-Twisting Sliding Mode Control for Acute Leukemia Therapy by Muhammad Munir Butt, Azhar Iqbal Kashif Butt

“…To enhance its performance, we introduce the RedFox Optimization Algorithm, a nature-inspired technique based on the hunting behavior of red foxes. …”
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Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing by Wenjing Guo, Cairong Yan, Ting Lu

“…Reinforcement-learning-based routing protocol takes advantage of the intelligent algorithm of reinforcement learning to search for the optimal routing path for data transmission. …”
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Multidimensional Resource Task Scheduling Based on Particle Swarm Optimization in Edge Computing by Zhonglu Zou, Zhuxin Zhai, Xin Yan, Zilin You, Liming Chen

“…The proposed approach enables the simultaneous scheduling of multiple tasks while iteratively adjusting the inertia weight and learning factors in the discrete particle swarm optimization (DPSO) algorithm. …”
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Dual-Layer Dynamic Optimization Model for Carbon-Conscious Transport Mode Allocation by Jing Gan, Dongmei Yan, Linheng Li

“…Within the framework of China’s “Dual Carbon” strategy, numerous cities have articulated visions and objectives for optimizing the travel structure of transport to further urban sustainable development goals. …”
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An Improved Large Neighborhood Search for Network-Level Airport Slot Allocation Optimization by Qiangzhe Wang, Yuanyuan Ma, Yifan Xu, Zhiyuan Shen, Dan Li

“…Validated through an extensive case study involving 4,695 requests across six hub airports, the algorithm achieves solutions within a 1.7% optimality gap while reducing computation time by up to 64%.…”
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