An Optimization Method for Green Permutation Flow Shop Scheduling Based on Deep Reinforcement Learning and MOEA/D by Yongxin Lu, Yiping Yuan, Adilanmu Sitahong, Yongsheng Chao, Yunxuan Wang

“…To improve the quality of solutions, the study first employs DRL to model the PFSP as a sequence-to-sequence model (DRL-PFSP) to obtain relatively better solutions. …”
Get full text

Maximum Torque per Ampere Control of PMSMs Using Real-Time Numerical Optimization by Yong Xu, Min-Yi Lin, Wen-Jie Wan, Yunchong Wang, Jian-Xin Shen

“…A flux-linkage based nonlinear PMSM model was developed to improve the torque control under dynamic conditions. …”
Get full text

Smart deep learning model for enhanced IoT intrusion detection by Faisal S. Alsubaei

“…The optimized SNN model also performed well on the NSL-KDD dataset with an accuracy of 99.0% and an AUC of 1.00. …”
Get full text

PCA-Kriging-Based Oscillating Jet Actuator Optimization and Wing Separation Flow Control by Qixiang Sun, Wanbo Wang, Jiaxin Pan

“…The optimization objectives are to improve the sweeping uniformity and range of the jet. …”
Get full text

A Smooth Jump Point Search Algorithm for Mobile Robots Path Planning Based on a Two-Dimensional Grid Model by Zhen Yang, Junli Li, Liwei Yang, Hejiang Chen

Get full text

Optimal Configuration Method for Electric-thermo-hydrogen System Considering Safety Risks by Chouwei NI, Yang CHEN, Xuesong ZHANG, Da LIN, Kaijian DU, Jian CHEN

“…Furthermore, the safety risk coefficient is used to convert the safety risk of the hydrogen storage tank into the objective function. The optimal configuration model of the ETHS is then established with the system investment cost, operation cost, and safety risk as optimization objectives, and the tabu chaotic quantum particle swarm optimization (TCQPSO) algorithm is employed to solve the model. …”
Get full text

Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making by Guanquan Zhu, Minyi Ye, Xinqi Yu, Junhao Liu, Mingju Wang, Zihang Luo, Haomin Liang, Yubin Zhong

“…Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. …”
Get full text

An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

“…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
Get full text

Midspan Deflection Prediction of Long-Span Cable-Stayed Bridge Based on DIWPSO-SVM Algorithm by Lilin Li, Qing He, Hua Wang, Wensheng Wang

“…The DIWPSO algorithm dynamically adjusts the inertia weight to balance global exploration and local exploitation, optimizing SVM parameters for improved performance. …”
Get full text

A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources by Zihao Wang, Shenhua Wang, Hanwen Ni, Junyin Wang, Jun Zhang

“…Additionally, an enhanced Kepler Optimization Algorithm (EKOA) was proposed, incorporating chaos mapping and adaptive learning rate strategies to improve search scope, convergence speed, and solution efficiency. …”
Get full text

Multi-Objective Optimization of Daylighting–Thermal Performance in Cold-Region University Library Atriums: A Parametric Design Approach by Yunong Gao, Shuting Zhao, Yong Huang, Hui Pan

“…In this paper, we take the library project in the cold region as a practical case, use the measured data to support the simulation experiment, combine the parametric platform and multi-objective coupling optimization algorithm to carry out digital modeling, and explore the dynamic relationship between the atrium light, heat environment, and the value of energy consumption under the influence of a variety of parameters. …”
Get full text

Improving the classification of a nanocomposite using nanoparticles based on a meta-analysis study, recurrent neural network and recurrent neural network Monte-Carlo algorithms by Rania Loukil, Wejden Gazehi, Mongi Besbes

Get full text

Optimization of Vessel Traffic Scheduling in a Compound Channel of an Estuarine Port with Opposing Distribution of Inner Anchorages and Terminals by Bolin Yin, Chengji Liang, Yu Wang, Xiaojie Xu, Yue Zhang

“…The entropy-weighted technique for order preference by similarity to ideal solution (TOPSIS) is used to calculate the objective weights of the Pareto frontier and identify the optimal solution. Experimental results show that the proposed model and algorithm yield optimal port entry and exit scheduling solutions. …”
Get full text

SMA-YOLO: An Improved YOLOv8 Algorithm Based on Parameter-Free Attention Mechanism and Multi-Scale Feature Fusion for Small Object Detection in UAV Images by Shenming Qu, Chaoxu Dang, Wangyou Chen, Yanhong Liu

“…Using YOLOv8n as the baseline, SMA-YOLO is evaluated on the VisDrone2019 dataset, achieving a 7.4% improvement in mAP@0.5 and a 13.3% reduction in model parameters, and we also verified its generalization ability on VAUDT and RSOD datasets, which demonstrates the effectiveness of our approach.…”
Get full text

Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…This paper proposes a cooperative sleep and energy-sharing strategy for heterogeneous 5G base station microgrid (BSMG) systems, utilizing deep learning and an improved multi-objective evolutionary algorithm based on decomposition (MOEA/D). …”
Get full text

Hybrid optimization for efficient 6G IoT traffic management and multi-routing strategy by J. Logeshwaran, Shobhit K. Patel, Om Prakash Kumar, Fahah Ahmed Al-Zahrani

“…Data was successfully routed using a hybrid Quantum Genetic Algorithm and Ant Colony Optimization (QGA-ACO) approach. …”
Get full text

The human-on-the-loop evaluation of multiobjective optimization algorithms for solving a real-world problem that integrates the food-energy-water nexus security and climate change... by Isaac Okola, Daniel Orwa Ochieng, Evans Kirimi Miriti, Gilbert Ouma Ong'isa

“…Such research areas include incorporating machine learning to predict, using performance data, the most suitable algorithm to solve a specific problem, and advancing interactive learning and user adjustments of the optimization process.…”
Get full text

Robust Optimization of Active Distribution Networks Considering Source-Side Uncertainty and Load-Side Demand Response by Renbo Wu, Shuqin Liu

“…The iCCG algorithm improves the computational efficiency by 35.2% compared with the traditional CCG algorithm, which verifies the effectiveness of the model in coping with the uncertainties and improving the economy and robustness.…”
Get full text

Proactive detection of anomalous behavior in Ethereum accounts using XAI-enabled ensemble stacking with Bayesian optimization by Vasavi Chithanuru, Mangayarkarasi Ramaiah

Get full text

Coordinated multi-objective optimization scheduling for electric vehicle swapping station cluster and grid by Xiang Liao, Ziyu Zheng, Beibei Qian, Haiwei Wang, Dianling Zhan, Junyi Shi, Chaoshun Li, Wei Huang

“…Meanwhile, an electricity mutual assistance strategy between EVBESS is proposed to improve overall energy efficiency. Subsequently, an improved many-objective optimization algorithm based on multiple update strategies (G-MOMUS) is used to solve the model. …”
Get full text