A multi-population multi-objective maritime inventory routing optimization algorithm with three-level dynamic encoding by Tianyu Liu, Jiaping Liu, He Xu

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Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints by Manqiong Sun, Yang Xu, Feng Xiao, Hao Ji, Bing Su, Fei Bu

“…The results demonstrate that the initial solutions obtained through the k-medoids clustering algorithm based on spatio-temporal distance improved the overall cost optimization by 1.85% and 4.74% compared to the other two algorithms. …”
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Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy by Yangqing DAN, Lei WANG, Weimin ZHENG, Jiahui WU, Chenxuan WANG, Gaowang YU

“…And then, based on the two-stage robust optimization theory, a strategy model for improving the hosting capacity of the power grid is constructed, and the column and constraint generation (C&CG) algorithm is used to solve the model. …”
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Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data by Zihan Zhou, Yanhong Guo, Yitao Wang, Jingfan Lyu, Haoran Gong, Xin Ye, Yachao Li

“…Our research integrates a priori knowledge of threat zone locations, speeds, and directions with real-time data on the UAVs position relative to the threat zones to effectively manage dynamic threat zones, allowing UAVs to dynamically decide whether to navigate around or through these zones, thus significantly reducing trajectory costs. To further improve search efficiency and solution quality, strategies such as greedy initialization and K-means clustering are incorporated, enhancing the algorithms multi-objective optimization capabilities. …”
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Effects of off-design performances and multiple market carbon trading mechanism on integrated energy systems with waste incineration power units by Jing Liu, Tong Zhao, Haolin Sui

“…Furthermore, to analyze effects of off-design performances and MMCTM on the electricity-gas-heating-cooling IES, five case studies have been conducted on a typical electricity-gas-heating-cooling IES and the improved slime mould algorithm (ISMA) were adopted. …”
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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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Advanced AI approaches for the modeling and optimization of microgrid energy systems by Mohammed Amine Hoummadi, Badre Bossoufi, Mohammed Karim, Ahmed Althobaiti, Thamer A. H. Alghamdi, Mohammed Alenezi

“…Three AI techniques, Genetic Algorithm (GA), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO), are employed to optimize the optimal composition of energy sources based on solar energy and wind energy, battery storage, and load profiles. …”
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ATHOS: A Hybrid Accelerator for PQC CRYSTALS-Algorithms Exploiting New CV-X-IF Interface by Alessandra Dolmeta, Maurizio Martina, Guido Masera

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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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Multi-objective layout optimization of hospital outpatient clinics based on NSGA II by Yanlin Zhao, Jiamei Gu

“…Abstract This study utilizes an improved NSGA-II algorithm to conduct a multi-objective optimization of the hospital outpatient department layout. …”
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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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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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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). …”

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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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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Cross-Domain Edge Computing Offloading Strategy for Delay-Optimized in Low Earth Orbit Satellite Network by YANG Guisong, HUANG Yechao, HE Xingyu

“…Existing approaches primarily employ centralized or distributed management, where the former suffers from high information collection latency and limited flexibility, while the latter incurs high inter-satellite collaboration costs, restricting global optimization. To address these challenges, an edge computing offloading process based on control domain partitioning is designed, and a latency-optimized cross-domain computing offloading strategy using the Actor-Critic algorithm is proposed. …”
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Enhanced multi-level K-means clustering and cluster head selection using a modernized pufferfish optimization algorithm for lifetime maximization in wireless sensor networks by Anjana Koyalil, Sivacoumar Rajalingam

“…A novel heuristic, the Modernized Pufferfish Optimization Algorithm (MPOA), is introduced to optimize WSN performance, drawing inspiration from the pufferfish's natural defense strategies. …”
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Multi-Objective Optimization of the Rotary Turning of Hardened Mold Steel for Energy Saving and Surface Roughness Improvements by Tat Khoa Doan, Trung Thanh Nguyen, An-Le Van

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A Framework for Low-Carbon Container Multimodal Transport Route Optimization Under Hybrid Uncertainty: Model and Case Study by Fenling Feng, Fanjian Zheng, Ze Zhang, Lei Wang

“…Subsequently, a multi-strategy improved whale optimization algorithm (WOA) is developed to solve the formulated model. …”
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Optimal Allocation of Hybrid Renewable Distributed Generation with Battery Energy Storage System Using MOEA/D-DRA Algorithm by P. Pon Ragothama Priya, S. Baskar, S. Tamil Selvi, C. K. Babulal

“…The proposed formulation for a Multi-objective Optimization of Hybrid Energy Sources allocation problem solved by the MOEA/D-DRA algorithm provides improved benefits like minimum annual energy loss, investment cost, CO2 emission, EENS by the DG units, and enhanced system voltage stability and voltage profile.…”
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