Web services composition algorithm based on the location of backup service and probabilistic QoS model by Hua WEN

“…For the service selection problem, an improved multiple objective optimization（MOO）algorithm was adopted to calculate the feasible solution set using clustering and QoS model. …”
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Charging pile fault prediction method combining whale optimization algorithm and long short-term memory network by Yansheng Huang, Atthapol Ngaopitakkul, Suntiti Yoomak

“…To solve the problem that traditional models tend to fall into locally optimal solutions (i.e., the model optimization process stays in the non-optimal regional minimum) in complex parameter space, the study innovatively proposes a hybrid prediction model that combines the whale optimization algorithm with the gated recurrent unit-long short-term memory neural network. …”
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Web services composition algorithm based on the location of backup service and probabilistic QoS model by Hua WEN

“…For the service selection problem, an improved multiple objective optimization（MOO）algorithm was adopted to calculate the feasible solution set using clustering and QoS model. …”
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An optimized method for short-term load forecasting based on feature fusion and ConvLSTM-3D neural network by Xiaofeng Yang, Shousheng Zhao, Kangyi Li, Wenjin Chen, Si Zhang, Jingwei Chen

“…As renewable energy continues to penetrate modern power systems, accurate short-term load forecasting is crucial for optimizing power generation resource allocation and reducing operational costs. …”
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Recent advancements in stereolithography (SLA) and their optimization of process parameters for sustainable manufacturing by Asmaul Husna, Salahuddin Ashrafi, ANM Amanullah Tomal, Noshin Tasnim Tuli, Adib Bin Rashid

“…Furthermore, the paper discusses the application of optimization methods like Genetic Algorithms and Artificial Neural Networks (ANN) to analyze, refine, and determine the optimal processing parameters for stereolithography. …”
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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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Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

“…This study introduces a hybrid AI-based optimization framework to enhance climbing perch aquaculture in smart farming systems, targeting improvements in both productivity and cost-efficiency. …”
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Optimizing Human-Centric Warehouse Operations: A Digital Twin Approach Using Dynamic Algorithms and AI/ML by Erhan Arslan

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Optimizing Container Repositioning Using a Sequential Insertion Algorithm for Pickup-Delivery Routing in Export-Import Operations by Ary Arvianto, Dihan Chofifah Cahyani, Dhimas Wachid Nur Saputra

“…The increasing number of empty containers significantly causes to traffic congestion and rising operational costs, thereby necessitating the development of an optimized routing model to enhance fleet utilization and minimize transportation expenses. …”
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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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Automated guided vehicle (AGV) path optimization method based on improved rapidly-exploring random trees by Zhigang Ren, Anjiang Cai, Feilong Xu

“…In response to the issues of low computational efficiency, slow convergence speed, curvy paths, and the tendency to fall into local optima in rapidly-exploring random tree (RRT) algorithms for automated guided vehicle (AGV) path planning, this article proposes an improved RRT algorithm that combines adaptive step-size optimization with K-dimensional tree (KD-Tree) based fast nearest neighbor search. …”
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OptiSGD-DPWGAN: Integrating Metaheuristic Algorithms and Differential Privacy to Improve Privacy-Utility Trade-Off in Generative Models by Alshaymaa Ahmed Mohamed, Yasmine N. M. Saleh, Ayman A. Abdel-Hamid

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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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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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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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Quad Rapidly-Exploring Random Tree Star Algorithm With Improved Potential Force for Unmanned Aerial Vehicle Path Planning by Peng Bian, Jiaming Fan, Yang Liu, Xia Chen, Yu Wang

“…Rapidly-exploring random tree star (RRT*) has attracted intensive attention in track planning due to its asymptotic optimal properties. However, the RRT* algorithm plans costly trajectory paths. …”
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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…This operation also reduces the computational cost by decreasing the amount of required feature map channels, while maintaining the effectiveness of the feature representation. (3) he Minimum Point Distance Intersection over Union loss function is employed to optimize bounding box detection during model training. (4) to construct the overall network structure, the Layer-wise Adaptive Momentum Pruning algorithm is used for thinning.ResultsExperiments on the TinyPerson dataset demonstrate that IYFVMNet achieves a 46.3% precision, 30% recall, 29.3% mAP50, and 11.8% mAP50-95.DiscussionThe model exhibits higher performance in terms of accuracy and efficiency when compared to other benchmark models, which demonstrates the effectiveness of the improved algorithm (e.g., YOLO-SGF, Guo-Net, TRC-YOLO) in small-object detection and provides a reference for future research.…”
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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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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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