A Non-Rigid Three-Dimensional Image Reconstruction Algorithm Based on Deformable Shape Reliability by Haiying Chen, Syed Atif Moqurrab

“…Most reconstruction algorithms for non-rigid three-dimensional (3D) images assume that non-rigidity can be represented as a linear combination of a fixed number of rigid bases. …”
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Sperm swarm optimization for many objective power flow problems with enhanced performance evaluation in power systems by Wulfran Fendzi Mbasso, Ambe Harrison, Pradeep Jangir, Idriss Dagal, Hossam Kotb, Njimboh Henry Alombah, Raman Kumar, Aseel Smerat, Emmanuel Fendzi Donfack, Saad F. Al-Gahtani, Z. M. S. Elbarbary

“…MaOSSO is shown to consistently outperform competing methods with up to 15–20% faster convergence and 25% less computation time. While applying the algorithm on the MaO-OPF problem, the active/reactive power loss minimization was optimized along with the voltage stability, emissions, operational cost, and Pareto front diversity sustaining. …”
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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…Feature selection is often used by some researchers to overcome these problems, because these methods have an important function in the process of reducing data dimensions and eliminating uncorrelated attributes that can cause noisy. Naive Bayes algorithm is used to support the process of determining the most optimal class. …”
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Metaheuristic Optimization of Wind Turbine Airfoils with Maximum-Thickness and Angle-of-Attack Constraints by Jinane Radi, Jesús Enrique Sierra-García, Matilde Santos, Carlos Armenta-Déu, Abdelouahed Djebli

“…The drag and lift coefficients are estimated, and a metaheuristic optimization technique, genetic algorithm, is applied to maximize the glide ratio while reducing the difference from the desired design parameters. …”
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Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning by I Nyoman Mahayasa Adiputra, Paweena Wanchai, Pei-Chun Lin

“…However, these methods have not performed well with classical machine learning algorithms. Methods To optimize the performance of classical machine learning on customer churn prediction tasks, this study introduces an extension framework called CostLearnGAN, a tabular generative adversarial network (GAN)-hybrid sampling method, and cost-sensitive Learning. …”
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IoT driven healthcare monitoring with evolutionary optimization and game theory by Shitharth Selvarajan, Hariprasath Manoharan, Taher Al-Shehari, Nasser A. Alsadhan, Subav Singh

“…By incorporating two evolutionary algorithms, the proposed approach optimizes the state of action for each participant while reducing energy consumption and processing delay. …”
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Adaptive optimization decision system for plate-fin heat Exchangers: An integrated approach to enhancing efficiency and performance by Na Sun, Shuai Zhang, Nan Li, Zijian Li, Meng He, Zhengchun Shen, Ke Wang, Xiaoyong Guo, Wen-Quan Tao

“…The GSA module uses the Sobol method to evaluate the impact of design variables on performance. The optimization module employs the Newton-Raphson-based optimizer (NRBO) and the multi-strategy improved grey wolf optimization algorithm (MIGWO). …”
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Adaptive Bayesian optimization for proportional derivative control in double-acting piston pump ventilators by Cong Toai Truong, Trung Dat Phan, Van Tu Duong, Huy Hung Nguyen, Thanh Truong Nguyen, Tan Tien Nguyen

“…Experimental results demonstrate that the proposed algorithm significantly improves system performance, reducing both tidal volume error and control cost compared to manual tuning. …”
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Smart building energy management with renewables and storage systems using a modified weighted mean of vectors algorithm by Mohamed Ebeed, Sabreen hassan, Salah Kamel, Loai Nasrat, Ali Wagdy Mohamed, Abdel-Raheem Youssef

“…Firstly, it employs the Elite Centroid Quasi-Oppositional Base Learning (ECQOBL) approach to improve the exploitation capabilities of conventional algorithms. …”
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Multi-objective multi-workflow task offloading based on evolutionary optimization by Teliekebieke Misha, Lisheng Sun, Zheng-yi Chai

“…Simulation results demonstrate that our algorithm optimally balances delay and energy consumption requirements compared to existing methods, while enhancing the diversity and convergence of non-dominated solutions.…”
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Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence by Manish Sharma Timilsina, Yuvraj Chaudhary, Prikshya Bhattarai, Bibek Uprety, Dilip Khatiwada

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Combining non-Monotone trust rregion method with a new adaptive radius for unconstrained optimization problems by Seyed Hamzeh Mirzaei, Ali Ashrafi

“…Purpose: One of the most effective methods for solving unconstrained optimization problems is the trust region method. …”
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A Chaotic Decomposition-Based Approach for Enhanced Multi-Objective Optimization by Javad Alikhani Koupaei, Mohammad Javad Ebadi

“…To address these issues, this paper proposes a chaotic decomposition-based approach that leverages the ergodic properties of chaotic maps to enhance optimization performance. The proposed method consists of three key stages: (1) chaotic sequence initialization, which generates a diverse population to enhance the global search while reducing computational costs; (2) chaos-based correction, which integrates a three-point operator (TPO) and a local improvement operator (LIO) to refine the Pareto front and balance the exploration–exploitation trade-offs; and (3) Tchebycheff decomposition-based updating, ensuring efficient convergence toward optimal solutions. …”
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Research on Multi-objective Shielding Intelligent Optimization Method Based on Non-dominated Sorting Genetic Algorithm NSGA-Ⅲ by WANG Mengqi, ZHENG Zheng, MEI Qiliang, PENG Chao, GAO Jing, ZHOU Yan

“…This study is dedicated to exploring an advanced intelligent multi-objective shielding optimization method based on the third generation non-dominated sorting genetic algorithm (NSGA-Ⅲ). …”

A multi-objective path optimization method for plant protection robots based on improved A*-IWOA by Jing Niu, Chuanyan Shen, Lipeng Zhang, Qijun Li, Haohao Ma

“…Methods To address the challenges of achieving low energy consumption and efficiency in path planning for plant protection robots operating in mountainous environments, a multi-objective path optimization approach was developed. This approach combines the improved A* algorithm with the Improved Whale Optimization Algorithm (A*-IWOA), utilizing a 2.5D elevation grid map. …”
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A Framework for Breast Cancer Classification with Deep Features and Modified Grey Wolf Optimization by Fathimathul Rajeena P.P, Sara Tehsin

“…A modified Grey Wolf Optimization algorithm with three significant adjustments improves feature selection and redundancy removal over the previous approach. …”
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Automated guided vehicle (AGV) path optimization method based on improved rapidly-exploring random trees by Zhigang Ren, Anjiang Cai, Feilong Xu

“…Firstly, an adaptive step-size optimization strategy is introduced to dynamically adjust the step size during node searches, improving both the planning quality and computational efficiency of the algorithm. …”
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Hybrid RSA-ROA Scheduling Algorithm for Minimization of Power Loss and Improving the Renewable with Sustainable Energy Harvesting in Power System by Cuddapah Anitha, Virendra Swaroop Sangtani, Ajay Kumar Bansal, Mahaveerakannan R., R. Rajesh Sharma, Saravanan M. S.

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Hybridization and Optimization of Bio and Nature-Inspired Metaheuristic Techniques of Beacon Nodes Scheduling for Localization in Underwater IoT Networks by Umar Draz, Tariq Ali, Sana Yasin, Muhammad Hasanain Chaudary, Muhammad Ayaz, El-Hadi M. Aggoune, Isha Yasin

“…The proposed framework, along with the hybridized metaheuristic algorithms, show great potential in improving node localization, optimizing scheduling, reducing energy costs, and enhancing reliable data delivery in the Internet of Underwater Things (IoUT)-based network.…”
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Improved particle swarm optimization for fractional order PID control design in robotic manipulator system: A performance analysis by Gamil Ahmed, Ahmed Eltayeb, Nezar M. Alyazidi, Imil Hamda Imran, Tarek Sheltami, Sami El-Ferik

“…The controller has undergone refinement and enhancement using state-of-the-art particle swarm optimization (PSO) techniques incorporating a cost function and a representative bio-inspired algorithm. …”
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