Research and Experimental Verification of an Efficient Subframe Lightweighting Method Integrating SIMP Topology and Size Optimization by Jihui Zhuang, Fan Zeng

“…A topology optimization model was established using the Solid Isotropic Material with Penalization (SIMP) method and solved using the Method of Moving Asymptotes (MMA) algorithm. …”
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Adaptive RFID Data Scheduling Using Proximal Policy Optimization for Reducing Data Processing Latency by Guowei Guo, Xinsen Yang, Ziwei Liang, Zeli Xi, Ximei Zhan, Peisong Li

“…This paper presents a novel approach for dynamically offloading data using deep reinforcement learning, specifically employing the Proximal Policy Optimization (PPO) algorithm. The proposed method utilizes a central controller equipped with the PPO model to make intelligent, real-time reader selection decisions based on environmental factors such as reader load, tag mobility, and network conditions. …”
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Semantic aware intelligent optimization for IRS/UAV-enabled MEC in wideband cognitive radio networks by Wei Zheng, Pengshan Ren, Qing Li

“…Particularly, the proposed optimization framework jointly optimizes UAV trajectories, subcarrier allocation, IRS reflection coefficients, task offloading ratios, task priorities and contextual relevance to maximize semantic utility and system energy efficiency while dynamically ensuring task demands. …”
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Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton by Yi Long, Zhi-jiang Du, Wei-dong Wang, Wei Dong

“…In this paper, a hybrid position control scheme, combining sliding mode control (SMC) with a cerebellar model articulation controller (CMAC) neural network, is proposed to control the exoskeleton to react appropriately to human motion intent. A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. …”
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Trajectory Planning Based on Screw Theory with Consideration of the Optimal Berth Position for a Space Robot by Yong Wang, Ying Liao, Kejie Gong

“…Then, objective functions are constructed. Finally, a genetic algorithm with a modified mutation operator is used to solve this optimization problem. …”
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Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization by Jing-Jing Liu, Jian-Chao Liu

“…The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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Machine learning approach for revealing the nickel grade and recovery optimization in reduction process of laterite ores by Vuri Ayu Setyowati, Fakhreza Abdul

“…This research attempts to take a machine learning approach to find the right model for process optimization. Data sets were collected from published studies that feature nickel ore grade (Ni and Fe content) and reduction process (temperature, additives, reductant, etc.), while prediction models for Ni grade and recovery were formed from four types of regression algorithms. …”
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Multi-objective optimization of low moisture food extrusion processing through active learning and robotics by Deborah Becker, Jean-Vincent Le Bé, Cornelia Rauh, Christoph Hartmann

“…The results of this study demonstrate an efficient approximation of those target properties within 15 iterations, while identifying optimal extrusion settings in a high-dimensional process space. …”
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Optimizing a Double Stage Heat Transformer Performance by Levenberg–Marquardt Artificial Neural Network by Suset Vázquez-Aveledo, Rosenberg J. Romero, Lorena Díaz-González, Moisés Montiel-González, Jesús Cerezo

“…This study aims to simultaneously optimize both user-defined parameters. Levenberg–Marquardt and scaled conjugated gradient algorithms were compared from five to twenty-five neurons to determine the optimal operating conditions while the coefficient of performance and the gross temperature lift were simultaneously maximized. …”
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Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response by Lei Chen, Man Yang, Yuqi Jiang, Shencong Zheng, Yifei Li, Xiaoyan You, Hongkun Chen

“…To address the challenge, this paper puts forward a two‐stage optimal scheduling model for the DCDNs considering flexible load response. …”
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Optimized Software Implementation of Keccak, Kyber, and Dilithium on RV{32,64}IM{B}{V} by Jipeng Zhang, Yuxing Yan, Junhao Huang, Çetin Kaya Koç

“… With the standardization of NIST post-quantum cryptographic (PQC) schemes, optimizing these PQC schemes across various platforms presents significant research value. …”
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RETRACTED: Temporal-Difference Graph-Based Optimization for High-Quality Reconstruction of MODIS NDVI Data by Shengtai Ji, Shuxin Han, Jiaxin Hu, Yuguang Li, Jing-Cheng Han

“…Regarding spatio-temporal NDVI data as a time-varying graph signal, the developed method utilized an optimization algorithm to maximize the spatial smoothness of temporal differences while preserving the spatial NDVI pattern. …”
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A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction by Gao Wang, Shuang Xu, Zixu Chen, Youzhu Li

“…This study proposes a hybrid forecasting model integrating variational mode decomposition (VMD), the Fruit Fly Optimization Algorithm (FOA), and a gated recurrent unit (GRU). …”
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A two-stage approach to enhancing biofuel supply chains through predictive and optimization analytics by Mehdi Soltani Tehrani, Siamak Noori, Ehsan Dehghani

“…Additionally, the Lagrangian relaxation technique is implemented to achieve precise solutions while preserving computational efficiency. For large-scale scenarios, the study leverages the non-dominated sorting genetic algorithm and multi-objective simulated annealing to generate near-optimal solutions. …”
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A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

“…This paper presents NSGA-III-GKM++, an advanced multi-objective optimization model that integrates the NSGA-III evolutionary algorithm with an enhanced K-means++ clustering technique to improve the convergence speed, solution diversity, and computational efficiency. …”
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Optimizing Long-Term Bank Financial Products Portfolio Problems with a Multiobjective Evolutionary Approach by Jian Xiong, Chao Zhang, Gang Kou, Rui Wang, Hisao Ishibuchi, Fawaz E. Alsaadi

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Optimization design of combustion chamber for a non-road diesel engine in high-altitude region by Yibing Hou, Jun Wang, Jilin Lei, Liang Chen

“…The optimized brake specific fuel consumption (BSFC) remained almost unchanged at this altitude, while nitrogen oxides (NOx) and soot emissions were reduced by 12.47 % and 3.23 %, respectively.…”
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Scheduling Optimization of Electric Rubber-Tired Vehicles in Underground Coal Mines Based on Constraint Programming by Maoquan Wan, Hao Li, Hao Wang, Jie Hou

“…This study presents a Constraint Programming (CP)-based optimization framework that integrates Virtual Charging Station Mapping (VCSM) and sensor fusion positioning to decouple spatiotemporal charging conflicts and applies a dynamic topology adjustment algorithm to enhance computational efficiency. …”
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Electromagnetic Analysis and Multi-Objective Design Optimization of a WFSM with Hybrid GOES-NOES Core by Kyeong-Tae Yu, Hwi-Rang Ban, Seong-Won Kim, Jun-Beom Park, Jang-Young Choi, Kyung-Hun Shin

“…Subsequently, a multi-objective optimization was conducted using Latin Hypercube Sampling, meta-modeling, and a genetic algorithm to maximize power density and efficiency while minimizing torque ripple. …”
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Research on Optimization Technology of Minimum Specific Fuel Consumption for Triple-Bypass Variable Cycle Engine by Haonan Guo, Yuhua Zhang, Bing Yu

“…In this paper, a multivariable steady-state controller was designed based on Model Predictive Control (MPC) to meet the needs of engine optimization control mode switching. The simulation results of the supersonic cruise mode show that the minimum fuel consumption control can reduce the fuel consumption of the engine by 2.6% while the thrust remains constant.…”
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