Constrained Bayesian Optimization: A Review by Sasan Amini, Inneke Vannieuwenhuyse, Alejandro Morales-Hernandez

“…Though it has been widely used to solve various optimization tasks, most of the literature has focused on unconstrained settings, while many real-world problems are characterized by constraints. …”
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GOAL ORIENTED SMART PORTFOLIO OPTIMIZATION by Ayush Deshpande, Rohan Gore, Sankirti Shiravale, Shubham Chougule, Samarth Bahirgonde

“…Portfolio optimization is a critical aspect of investment strategy, which aims to maximize returns while minimizing risk. …”
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Short term traffic flow prediction and timing optimization at signalized intersections based on SG-LSTM and particle swarm optimization by Lei Yang, Ruijun Guo

“…The optimized signal timing scheme is derived through the implementation of the particle swarm optimization algorithm in Matlab. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…Abstract This study aims to enhance computational performance while minimizing environmental impact in AI (Artificial Intelligence) and ML (Machine Learning) applications, especially in cybersecurity, by developing energy-efficient models using a multi-objective optimization approach. …”
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Sensitivity Analysis Based on E-TOPSIS Combined with MORIME-Based Multi-Objective Optimization for Sprayer Frame Design Optimization by Shaohao Zhou, Qi Chen, Lihua Zhang

“…Finally, the multi-objective lightweight design of the selected components was performed based on the MORIME algorithm. After optimization, the stress increased by 12.01% and 1.52% under two operating conditions, while deformation increased by 0.647 mm and 0.607 mm, and the frame mass was reduced by 22.754 kg, a decrease of 12.8%. …”
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Qualitative Simulation Algorithm for Resource Scheduling in Enterprise Management Cloud Mode by Jiaohui Yu

“…Aiming at the problem of resource scheduling optimization in enterprise management cloud mode, a customizable fuzzy clustering cloud resource scheduling algorithm based on trust sensitivity is proposed. …”
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Model for virtual corporations partner selection based on adaptive genetic algorithm by LI Jian1, JING Bo2, NIU Shao-zhang1, YANG Yi-xian1

“…To enhance the efficiency of corporation partner selection and optimization process in virtual corporations, an partner selection process and optimizations model for virtual corporations based on adaptive genetic algorithm were pre-sented. …”
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Fault Detection of Aircraft Control System Based on Negative Selection Algorithm by Jie Chen, Senyao Chen, Cunbao Ma, Zhengdong Jing, Qingshan Xu

“…The aircraft control system controls the whole flight movement process. Its fault detection can assist the aircraft PHM system in making decisions and completing the targeted maintenance, which is of great significance to improve the safety and reliability of the aircraft. …”
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Generation of Sparse Antennas and Scatterers Based on Optimal Current Grid Approximation by Tuan Phuong Dang, Manh Tuan Nguyen, Adnan F. Alhaj Hasan, Talgat R. Gazizov

“…To solve this task, we present a novel algorithm based on the optimal current grid approximation for generating sparse scattering structures and evaluating their effectiveness. …”
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Beamforming algorithm for cognitive satellite and terrestrial network based on UAV relay by Yanli LI, Zhi LIN, Zining WANG, Ba XU, Ming CHENG, Jian OUYANG

“…Two beamforming (BF) schemes to achieve spectrum sharing by suppressing inter-system interferences in cognitive satellite and terrestrial networks were proposed, where the satellite and UAV cooperative network was used as the secondary network, while the terrestrial network was used as the primary network.Specifically, considering that only the statistical channel state information was available, a constrained optimization problem was formulated to maximize the signal-to- interference-plus-noise ratio of the secondary user under the constraints of the maximum transmit power at the UAV and the interference power of the primary user.Then, an iteration-based BF scheme was proposed to solve the constrained optimization problem.To reduce the computational complexity of the iterative algorithm, a zero-forcing based BF scheme was further proposed.Finally, computer simulations verify the correctness and effectiveness of the proposed BF schemes.…”
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Precise wind allocation scheme decision based on attraction-repulsion algorithm by NI Jingfeng, CHEN Dunwei, LIU Yujiao

“…To address the issue of fluctuating branch airflow in the ventilation system caused by changes in mine ventilation facilities and air network structure during underground production operations, which in turn leads to insufficient airflow at consumption points, a precise wind allocation algorithm based on the Attraction-Repulsion Optimization Algorithm (AROA) is proposed. …”
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Medium and Long Term Wind Power Prediction Based on Graph Convolutional Network and Wind Velocity Differential Fitting by Zihan CHEN, Wei TENG, Xuefeng XU, Xian DING, Yibing LIU

“…In order to make full use of the prior relationships among data features and improve the prediction accuracy of medium and long term wind power at wind farms, a medium and long term wind power prediction model based on graph convolution neural network (GCN), wind velocity differential fitting (DF), and particle swarm optimization (PSO) is proposed. By analyzing the whole process of wind power generation, the influencing factors of wind power and the interrelation among them are explored, and the GCN model is built. …”
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Topology optimization of a cargo gripper design using the minimum effort principle by Gnezdilov S.G.

“…The primary goal of the research is to enhance the stiffness and reliability of the structure while reducing its mass. The left gripper arm, subjected to complex loading conditions, is selected as the optimization object. …”
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A Systematic Review and Evaluation of Sustainable AI Algorithms and Techniques in Healthcare by Yehia Ibrahim Alzoubi, Ahmet E. Topcu, Ersin Elbasi

“…This systematic review paper categorizes and classifies AI algorithms and tools in the healthcare sector to support more sustainable practices, focusing on reducing energy use while maintaining high standards in diagnostic accuracy and patient outcomes. …”
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Simultaneous Multi-Objective and Topology Optimization: Effect of Mesh Refinement and Number of Iterations on Computational Cost by Daniel Miler, Matija Hoić, Rudolf Tomić, Andrej Jokić, Robert Mašović

“…Due to repeated topology optimization calls within the genetic algorithm, the computational cost is significant. …”
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Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons by Coulon Romain

“…The Genetic Algorithm (GA), a novel optimization-based approach, demonstrates exceptional resilience to outliers. …”
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Scalable PBFT-like algorithm for trust management of degree/graduation certificates by ZHANG Xuewang, LEI Zhitao, LIN Jinzhao

“…Analysis and simulation experiments demonstrate that the proposed algorithm ensures security while achieving higher throughput and scalability in large-scale applications of degree/graduation certificate trust management.…”
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Quantum Circuit Synthesis Using Fuzzy-Logic-Assisted Genetic Algorithms by Ishraq Islam, Vinayak Jha, Sneha Thomas, Kieran F. Egan, Alvir Nobel, Serom Kim, Manu Chaudhary, Sunday Ogundele, Dylan Kneidel, Ben Phillips, Manish Singh, Kareem El-Araby, Devon Bontrager, Esam El-Araby

“…Therefore, interest has grown towards heuristics-based synthesis techniques, which are able to produce approximations of the desired algorithm, while optimizing depth and gate-count. In this work, we investigate using genetic algorithms (GA)—a proven gradient-free optimization technique based on natural selection—for circuit synthesis. …”
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Packet-loss robust scalable authentication algorithm for compressed image streaming by Xiao-wei YI, Heng-tai MA, Gang ZHENG, Chang-wen ZHENG

“…Finally, these hash values of decoding-independent packets and the digital signature of the whole bitstream are encoded with an error-correction coding algorithm. …”
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Evolutionary search algorithm for learning activation function of an artificial neural network by Yurshin Viacheslav

“…The proposed method aims to enhance the efficiency of the search process for optimal activation functions. Our algorithm employs genetic programming to evolve the general form of activation functions, while gradient descent optimizes their parameters during network training. …”
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