Nonlinear Model Predictive Control for Trajectory Tracking of Omnidirectional Robot Using Resilient Propagation by Mahmoud El-Sayyah, Mohamad R. Saad, Maarouf Saad

“…This paper proposes an enhanced Nonlinear Model Predictive Control (NMPC) framework that incorporates a robust, convergent variant of the resilient propagation (RPROP) algorithm to efficiently solve the Nonlinear Optimization Problem (NOP) in real time. The controller is developed for both constrained and unconstrained trajectory tracking of Wheeled Mobile Robots (WMRs), with operational constraints handled via the external penalty method. …”
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Train timetable and stopping plan generation based on cross-line passenger flow in high-speed railway network by Yuqiang Wang

“…In addition, we regard train disturbances in different directions as different train headways at cross-line stations to optimize train scheduling practically. Sequentially, a mixed-integer linear programing model with headway and coupling constraints is formulated. …”
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Interference Control for Cognitive Network with High Mobility by Yuanxuan Li, Gang Zhu, Siyu Lin, Ke Guan, Bo Ai

“…The proposed IC schemes of the secondary system are converted to the power allocation problems, and then they are formulated to optimization problem whose objects are to maximize the capacity of the secondary system with the interference constraints. …”
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Anatomy of Deep Learning Image Classification and Object Detection on Commercial Edge Devices: A Case Study on Face Mask Detection by Dimitrios Kolosov, Vasilios Kelefouras, Pandelis Kourtessis, Iosif Mporas

“…Developing efficient on-the-edge Deep Learning (DL) applications is a challenging and non-trivial task, as first different DL models need to be explored with different trade-offs between accuracy and complexity, second, various optimization options, frameworks and libraries are available that need to be explored, third, a wide range of edge devices are available with different computation and memory constraints. …”
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Time-Dependent Vehicle Routing of Free Pickup and Delivery Service in Flight Ticket Sales Companies Based on Carbon Emissions by Jingmei Guo, Chao Liu

“…The problem consists of routing a fleet of vehicles in order to deliver a set of customers to the airport considering the traffic congestion, time window constraints, and maximum ride time constraints. …”
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Encoding Coefficient Similarity-Based Multifeature Sparse Representation for Finger Vein Recognition by Lizhen Zhou, Lu Yang, Deqian Fu, Gongping Yang

“…Furthermore, the proposed method is capable of fusing all kinds of features, not limited to specific ones. The optimization problem of the proposed method is efficiently solved using the alternating direction multiplier method algorithm. …”
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Experimental Application of Predictive Controllers by C. H. F. Silva, H. M. Henrique, L. C. Oliveira-Lopes

“…The basic characteristic of these algorithms is the formulation of an optimization problem in order to compute the sequence of control moves that minimize a performance function on the time horizon with the best information available at each instant, taking into account operation and plant model constraints. …”
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HCDRNN-NMPC: A New Approach to Design Nonlinear Model Predictive Control (NMPC) Based on the Hyper Chaotic Diagonal Recurrent Neural Network (HCDRNN) by Samira Johari, Mahdi Yaghoobi, Hamid R. Kobravi

“…The proposed scheme uses an improved gradient method to solve the optimization problem in NMPC. The proposed control is used to control six degrees of freedom Stewart parallel robot with hard-nonlinearity, input constraints, and in the presence of uncertainties including external disturbance. …”
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Compressive Sensing of Multichannel Electroencephalogram Signals Based on Nonlocal Low-Rank and Cosparse Priors by Jun Zhu, Lei Feng, Chunmeng Wang

“…The Alternating Direction Method of Multipliers (ADMM) are also used to efficiently solve the resulting non-convex optimization problem. The outcomes of the experiments unequivocally demonstrate that by using NLRC, the quality of signal reconstruction is significantly enhanced.…”
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CHIP: Clustering Hotspots in Layout Using Integer Programming by Rohit Reddy Takkala, Chris Chu

“…However, the clusters generated from generic clustering algorithms need not achieve optimal results. In this paper, we introduce two optimal integer linear programming formulations based on triangle inequality to solve the problem of minimizing cluster count while satisfying given constraints. …”
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A Multiobjective Evolutionary Algorithm for Energy-Efficient Cooperative Spectrum Sensing in Cognitive Radio Sensor Network by Weirong Liu, Gaorong Qin, Shuo Li, Jian He, Xiaoyong Zhang

“…By constructing a comprehensive performance metric, the joint optimization is transferred to a multiobjective optimal problem, in which the sleeping schedule and censoring mechanism are taken into consideration. …”
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Robust Constrained Model Predictive Control for T-S Fuzzy Uncertain System with Data Loss and Data Quantization by Hongchun Qu, Yu Li, Wei Liu

“…The developed MPC algorithm can guarantee the recursive feasibility of the optimization problem and the stability of closed-loop system simultaneously. …”
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Research on boosting self-sustainability for RIS-aided multi-cluster wireless powered communication networks by SHAO Kai, MAO Tiantian, WANG Guangyu, CHU Zheng

“…A nonlinear energy harvesting (NLEH) model was adopted in the established optimization problem, with constraints on phase shift error (PSE) of RIS, transmission time SNR of users, and imperfect channel state information (CSI). …”
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Enhancing Information Freshness and Energy Efficiency in D2D Networks Through DRL-Based Scheduling and Resource Management by Parisa Parhizgar, Mehdi Mahdavi, Mohammad Reza Ahmadzadeh, Melike Erol-Kantarci

“…We introduce a novel model for joint scheduling and resource management in D2D networks, taking into account environmental constraints. To preserve information freshness, measured by minimizing the average age of information (AoI), and to effectively utilize energy harvesting (EH) technology to satisfy the network's energy needs, we formulate an online optimization problem. …”
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NAVA: A Network-Adaptive View-Aware Volumetric Video Streaming Framework by Nguyen Long Quang, Truong Thu Huong, Duc Nguyen

“…In our framework, multiple versions with different quality of individual volumetric video are prepared and stored on the server in advance. The rate allocation problem is formulated as a optimization problem by taking into account the visible area of individual sequences as well as the network constraint. …”
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A Study of Multi-distributed Resource Equalization Allocation for Virtual Power Plants Based on Genetic-heuristic Algorithm by Haifeng Li, Tao Jin, Xian Xu, Lin Shi

“…Abstract A multi-resource balanced allocation method using a genetic-heuristic fusion algorithm is proposed to address the imbalance in distributed power generation resource allocation and the over-generation problem in virtual power plants. By establishing models of wind, solar, storage, and controllable load characteristics, an optimization model is constructed with objectives of resource allocation balance and minimization of call costs, subject to constraints such as power balance. …”
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Capacity Allocation Method for Wind-Solar-Hydro-Storage Complementary System Considering Time and Spatial Transfer Characteristics of Load by Jie WEN, Jichun LIU, Zhengnan WEN, Jianhua LI, Chenxin LI

“…Finally, through a case simulation, the nonlinear optimization problem is solved by professional optimization software (LINGO), and the allocation capacities of the source end system under different planning years and scenarios are obtained, which has verified the effectiveness of the proposed method in improving the system indicators.…”
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A Predictive Approach for Enhancing Accuracy in Remote Robotic Surgery Using Informer Model by Muhammad Hanif Lashari, Shakil Ahmed, Wafa Batayneh, Ashfaq Khokhar

“…The method integrates the optimization problem into the Informer model by embedding constraints such as energy efficiency, smoothness, and robustness into its training process using a differentiable optimization layer. …”
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Knowledge- and Model-Driven Deep Reinforcement Learning for Efficient Federated Edge Learning: Single- and Multi-Agent Frameworks by Yangchen Li, Lingzhi Zhao, Tianle Wang, Lianghui Ding, Feng Yang

“…We formulate a joint optimization problem for FL worker selection and algorithm parameter configuration to minimize the final test loss subject to time and energy constraints. …”
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A Full-Profile Measurement Method for an Inner Wall with Narrow-Aperture and Large-Cavity Parts Based on Line-Structured Light Rotary Scanning by Zhengwen Li, Changshuai Fang, Xiaodong Zhang

“…Considering the structural constraints in the measurement of narrow-aperture and large-cavity parts, a structural optimization algorithm is designed to enable the sensor to achieve a high theoretical measurement resolution while satisfying the geometric constraints of the measured parts. …”
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