FONDUE—Fine-Tuned Optimization: Nurturing Data Usability & Efficiency by Valerie Restat, Indra Diestelkämper, Meike Klettke, Uta Störl

“…As an adaptive and easily extendable framework, FONDUE operates similarly to proven methods of database query optimization. Analogously, it consists of the following parts: Rule-based optimization, where the appropriate data cleaning algorithms are selected based on use case constraints, optimizer hints in the form of best practices, and cost-based optimization, where the costs are measured in terms of data quality. …”
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Generative Design-Driven Optimization for Effective Concrete Structural Systems by Hossam Wefki, Mona Salah, Emad Elbeltagi, Majed Alinizzi

“…This research introduces a parametric algorithmic model for the automated optimization of RC buildings with solid slab systems. …”
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Non-Vertical Well Trajectory Design Based on Multi-Objective Optimization by Xiaowei Li, Yu Li, Yang Wu, Zhaokai Hou, Haipeng Gu

“…The optimization and control of the wellbore trajectory is one of the important technologies to improve drilling efficiency, reduce drilling cost, and ensure drilling safety in the process of modern oil and gas exploration and development. …”
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Stability Analysis and Construction Parameter Optimization of Tunnels in the Fractured Zone of Faults by Banma Huang, Haibo Chen, Chenglong Duan, Wenhu Li

“…In order to improve the construction method of highway tunnel fault, improve the excavation level, improve the construction efficiency, reduce the project cost, and shorten the construction period, so as to find a specific road, this paper puts forward the research method of tunnel stability analysis and construction parameter optimization in the fault fracture zone. …”
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Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning by Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis

“…These algorithms are computationally costly, so we split optimization into an offline phase (costly pre-training for a route) and an online phase where the algorithms are fine-tuned as updated weather data become available. …”
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Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs by Kaifeng Geng, Chunming Ye, Zhen hua Dai, Li Liu

“…This paper proposes an improved multiobjective ant lion optimization (IMOALO) algorithm to solve the RHFSP with the objectives of minimizing the makespan and energy consumption cost under Time-of-Use (TOU) electricity tariffs. …”
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Optimization of external container delivery and pickup scheduling based on appointment mechanism. by Pengfei Huang, Hao Wang, Fangjiao Tan, Yuyue Jiang, Jinfen Cai

“…Through case studies, we have demonstrated the superior performance of this algorithm in addressing relevant problems. The results show that, in terms of truck operational costs, the improved algorithm reduces costs by 10.96% and 3.02% compared to traditional Ant Colony Optimization and Variable Neighborhood Search algorithms, respectively, and by 4.89% compared to manual scheduling. …”
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Multi-objective Optimization Design of Component Cooling System in HPR1000 by ZHAO Weiguang1, 2, YU Pei1, 3, ZENG Xiaobo1, 2, FAN Guangming1, 2, YAN Changqi1, 2

“…To manage this complexity, a novel optimization algorithm was implemented to perform multi-objective optimization. …”
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Application of deep reinforcement learning in parameter optimization and refinement of turbulence models by Zhan Zhang

“…The aim of this study is to improve the accuracy of simulations by optimizing turbulence model parameters, in order to address the cost and time limitations of traditional wind tunnel tests and on-site measurements. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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Research on pose estimation algorithm of non-cooperative target tracked vehicles based on PnP model by Zhigang Ren, Xinagjun Tang, Guoquan Ren, Dinghai Wu

“…Finally, the pose equation is solved by finding the local minimum of the cost function through algebraic optimization, thus avoiding convergence issues in iterative optimization. …”
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Optimal PMU Placement Considering with HVDC Links and Their Voltage Stability Requirements by Milad Dalali, Hosein Kazemi Karegar

“…However, it is not practical in real networks due to the relatively expensive cost of PMUs and other technical limitations. Optimal PMU Placement (OPP) is an optimization problem providing full observability of the power network with minimum number of PMUs. …”
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Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer by César Feniou, Muhammad Hassan, Baptiste Claudon, Axel Courtat, Olivier Adjoua, Yvon Maday, Jean-Philip Piquemal

“…However, practical implementations on current quantum processing units (QPUs) are challenging due to the noisy evaluation of a polynomially scaling number of observables, undertaken for operator selection and high-dimensional cost function optimization. We introduce an adaptive algorithm using analytic, gradient-free optimization, called Greedy Gradient-free Adaptive VQE (GGA-VQE). …”
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Smart energy management for revenue optimization and grid independence in an Indian RDS by T. Yuvaraj, M. Thirumalai, M. Dharmalingam, Sudhakar Babu Thanikanti, Sanjeevikumar Padmanaban

“…A comparative analysis with alternative optimization algorithms demonstrates HPOA’s superiority in convergence speed, computational efficiency, and energy cost reduction. …”
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Multi-Attribute Collaborative Optimization for Multimodal Transportation Based on User Preferences by Youpeng Lu, Gang Gao

“…In terms of solution methods, an improved Genetic Algorithm (GA) and Aptenodytes Forsteri Optimization (AFO) hybrid algorithm (GA-AFO) is proposed, which introduces GA to generate a high-quality initial population to accelerate convergence. …”
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Conveyor X-Ray Tomosynthesis Imaging With Optimized Structured Sequential Illumination by Xu Ma, Dong Wang, Angela Cuadros, Tianyi Mao, Qile Zhao, Gonzalo R. Arce, Tingfa Xu

“…The optimized structured sequential illumination is proved to significantly improve the imaging performance of the conveyor X-ray tomosynthesis system based on a set of simulations.…”
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Optimization Techniques on Quantum and Classical Systems: A Comprehensive Comparative Study by Shaik Hussain, Rajitha Morampudi, Priyamvada K., Bhargavi R. Naveena

“…This study compares Particle Swarm Optimization (PSO), Moth Flame Optimization (MFO), and Genetic Algorithm (GA) on three platforms : a local computer, a local computer with quantum integration, and an IBM quantum machine. …”
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An Efficient Path Planning Algorithm Based on Delaunay Triangular NavMesh for Off-Road Vehicle Navigation by Ting Tian, Huijing Wu, Haitao Wei, Fang Wu, Jiandong Shang

“…Considering that the improved road-off path planning A* algorithm could identify a chain of path triangles for calculating the shortest path, the funnel algorithm was then introduced to transform the path planning problem into a dynamic geometric problem, iteratively approximating the optimal path by maintaining an evolving funnel region, obtaining a shortest path closer to the Euclidean shortest path. …”
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FCMI-YOLO: An efficient deep learning-based algorithm for real-time fire detection on edge devices. by Junjie Lu, Yuchen Zheng, Liwei Guan, Bing Lin, Wenzao Shi, Junyan Zhang, Yunping Wu

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. Firstly, the FasterNext module is proposed to reduce computational cost and enhance detection precision through lightweight design. …”
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Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority by Xiaoye Zhou, Yuhao Feng

“…Second, a two-stage hybrid algorithm is proposed for the problem model. In the first stage, the deep neural network and the grid search improved support vector machine algorithm (DNN-GSM-SVM) are used to screen and classify customer priority features, and in the second stage, adaptive large-scale neighborhood search improved genetic algorithms (ALNS-GA) are used to solve the problem of vehicle-drone joint distribution path planning problem. …”
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