Distributionally robust optimal scheduling of flexible distribution networks considering dynamic spatio-temporal correlation of renewable energy by Shunxiang Yu, Xiaoming Dong, Chengfu Wang, Tianguang Lu

“…By utilizing the 1-norm and ∞-norm to characterize the uncertainty sets between sources and loads, this strategy effectively minimizes operational costs while ensuring robust performance. The proposed model is linearized and relaxed through second-order cone programming and solved using the column and constraint generation (C&CG) algorithm. …”
Get full text

Geometry optimization on the cross section of adhesively bonded thin-walled composite beam subjected to axial crushing load by Xiao Han, Jingru Ye, Shaoqiang Hou, Wenbin Hou

“…The minimum total material cost and maximum energy absorption (EA) during the axial crushing test of the CFRP beam were selected as the optimization objectives. The non-dominated sorting genetic algorithm II (NSGA-II) was introduced to search for global optimum solution, and radial basis function (RBF) approximations for the objective functions were applied to reduce the computational cost. …”
Get full text

Leveraging machine learning for prediction and optimization of texture properties of sustainable activated carbon derived from waste materials by Ahmed Farid Ibrahim, Mohamed Abdrabou Hussein

“…A genetic algorithm (GA) integrated with the GBR model optimizes the synthesis process. …”
Get full text

Numerical analysis of flow heat transfer characteristics and optimization of double-layered microchannel heat sinks with different structures by Bo Cai, Pan Hu, Yifan Li, Bingzhi Chen, Haoyang Cai

“…The structural parameters of TMC-ORTC are optimized by multi-objective genetic algorithm with thermal resistance, pumping power and temperature uniformity as optimization objectives. …”
Get full text

A Digital Twin Framework With Meta- and Transfer Learning for Scalable Multi-Machine Modeling and Optimization in Semiconductor Manufacturing by Chin-Yi Lin, Tzu-Liang Tseng, Tsung-Han Tsai

“…This study introduces MOODFG-MLTL, an innovative algorithm that integrates Meta-Learning and Transfer Learning within a Multi-Objective Optimization using Deep-Feature Gaussian Processes (MOODFG) architecture. …”
Get full text

Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment by Nabeeha Qayyum, Umar Jamil, Anzar Mahmood

“…A genetic algorithm (GA) based optimization technique was employed to evaluate the performance of a HEMS and validated with particle swarm optimization (PSO) technique under identical initial conditions for each appliance and their corresponding energy pricing over different periods. …”
Get full text

Capacity Optimization and Location of BESS-SC Hybrid System for Grid Inertia Support With High Wind Power Penetration by Shami Ahmad Assery, Nan Chen, Xiao-Ping Zhang

“…This paper firstly proposes a sizing strategy based on techno-economic analysis using the Genetic Algorithm (GA) optimization technique, which can minimize the cost of the BESS-SC hybrid system while maintaining the Rate of Change of Frequency (RoCoF) within an acceptable limit. …”
Get full text

Collaborative optimization of signals and ecological driving speed guidance for buses without dedicated bus lanes in the connected environment by Hui Li, Yunfei Ge, Yuzhou Duan, Xu Zhang

“…Building upon this, optimal timings for phase adjustments and the optimization bus trajectories are calculated using signal control and eco-driving speed guidance models. …”
Get full text

Electricity Carbon Coupled Market Modeling Method and Market Optimization Mechanism Based on Dynamic Carbon Emission Intensity by Tong ZHAO, Xuesong LI, Hao ZHOU, Yu DING, Bin YANG, Wentao WANG, Peng WANG

“…A Markov decision iterative optimal coordination algorithm (MDIOCA) is proposed to solve the model. …”
Get full text

Performance Optimization of Synchronous Reluctance Motor using Adaptive MTPA Curve Fitting with Anti-Windup Current Control by Alex V, Rammohan A

“…Conventional scalar control methods typically rely on precomputed lookup tables or iterative optimization algorithms, which introduce computational overhead and require significant memory resources. …”
Get full text

Lattice-Based Certificateless Proxy Re-Signature for IoT: A Computation-and-Storage Optimized Post-Quantum Scheme by Zhanzhen Wei, Gongjian Lan, Hong Zhao, Zhaobin Li, Zheng Ju

“…However, most existing proxy re-signature schemes, which are predominantly based on traditional public-key cryptosystems, face security vulnerabilities and certificate management bottlenecks. While identity-based schemes alleviate some issues, they introduce key escrow concerns. …”
Get full text

Bioinspired Mobility-Aware Clustering Optimization in Flying Ad Hoc Sensor Network for Internet of Things: BIMAC-FASNET by Abdu Salam, Qaisar Javaid, Masood Ahmad

“…First, the clustering problem in network is formulated to dynamic optimization problem. An algorithm is designed based on bee intelligence, applied to select optimal UAVs CH and balanced cluster. …”
Get full text

A hybrid prediction and multi-objective optimization framework for limestone calcined clay cement concrete mixture design by Xi Chen, Weiyi Chen, Zongao Li, Pu Zhang

“…Non-dominated Sorting Genetic Algorithm-II was employed for MOO, generating Pareto fronts to minimize cost and embodied carbon while meeting strength requirements. …”
Get full text

Pore size classification and prediction based on distribution of reservoir fluid volumes utilizing well logs and deep learning algorithm in a complex lithology by Hassan Bagheri, Reza Mohebian, Ali Moradzadeh, Behnia Azizzadeh Mehmandost Olya

“…So, all three feature selection algorithms introduced the number of 4 logs as the most optimal number of inputs to the DL algorithm with different combinations of logs for each of the three desired outputs. …”
Get full text

Robust Optimal Control for a Microbial Batch Culture Processes: Incorporating Free Terminal Time and Sensitivity Analysis by Yang Qi, Zheng Shijin, Xie Suzhen, Feng Enmin

“…Subsequently, we develop an improved particle swarm optimization algorithm to solve this equivalent problem. …”
Get full text

Optimization of diagnostics of retinopathy of prematurity stages based on the integration of clinical data using the Key to Diagnosis I software by O. A. Pererva, M. A. Kovalevskaya

Get full text

Multi-objective optimization of lithium-ion battery designs considering the dilemma between energy density and rate capability by Xiao-Ying Ma, Wen-Ke Zhang, Ying Yin, Kailong Liu, Xiao-Guang Yang

“…A physics-based pseudo-2D model, validated against experimental data, generates data to train the surrogate model, which is combined with the NSGA-II algorithm for rapid optimization. Three different objective calculation methods are compared to identify the maximum sum of energy densities, lowest polarization, and most balanced performance, respectively. …”
Get full text

Hybrid active-passive thermal management system for deep wells: Long-term stability and multi-objective optimization by Zongwei Yao, Haomin Li, Hongxu Xu, Hongfei Yang, Qiushi Bi, Tianshuang Xu

“…To address this challenge, this study proposes a hybrid active-passive thermal management system integrating vacuum insulation, phase change materials (PCMs), and an optimized curved flow channel. A multi-objective optimization framework combining Kriging surrogate modeling and NSGA-II algorithm is developed to maximize heat transfer coefficient (h) while minimizing pressure drop (P). …”
Get full text

Physics-informed modeling and process optimization of friction stir welding of AA7075-T6 with a zinc interlayer by Dejene Alemayehu Ifa, Dame Alemayehu Efa, Naol Dessalegn Dejene, Sololo Kebede Nemomsa

“…This study is the first to combine a zinc interlayer with machine learning (ML) based optimization in the FSW of AA7075-T6. Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest Regression (RFR), a Genetic Algorithm (GA) for optimization, and Response Surface Methodology (RSM) for statistical modeling were used to analyze a dataset of 60 observations. …”
Get full text

Personalized EEG-guided brain stimulation targeting in major depression via network controllability and multi-objective optimization by Aihua Wang, Jingnan Sun

“…A multi-objective optimization algorithm (NSGA-II) was used to select optimal node–frequency–amplitude combinations minimizing control energy while maximizing network efficiency gain and structural restoration. …”
Get full text