Dimensionality Reduction Optimization of High Subsonic Unmanned Aerial Vehicles Intake by Zeqi QI, Zheng GUO, Suqi CHEN, Ke YU

“…Among them, sensitivity analysis is suitable for dimensionality reduction with a clear optimization objective, while PCA is more suitable for dimensionality reduction in multi-objective optimization.…”
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16-channel photonic solver for optimization problems on a silicon chip by Jiayi Ouyang, Shengping Liu, Ziyue Yang, Wei Wang, Xue Feng, Yongzhuo Li, Yidong Huang

“…The photonic chip is employed to perform the optical vector-matrix multiplication (OVMM) to calculate the cost function of the QUBO problem, while the electronic processor runs the heuristic algorithm to search for the optimal solution. …”
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Optimized planning of electric vehicle charging infrastructure for grid performance improvement by Mohammad Reza Maghami, Ka Fei Thang, Arthur G. O. Mutambara, Ali Akbar Firoozi, Elnaz Yaghoubi, Mehdi Zareian Jahromi, Elaheh Yaghoubi

“…This paper presents a multi-objective optimization framework developed using particle swarm optimization (PSO) algorithm to determine optimal placement and capacity of EV charging infrastructures. …”
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Quantum Adiabatic Optimization with Rydberg Arrays: Localization Phenomena and Encoding Strategies by Lisa Bombieri, Zhongda Zeng, Roberto Tricarico, Rui Lin, Simone Notarnicola, Madelyn Cain, Mikhail D. Lukin, Hannes Pichler

“…However, these Hamiltonians are often incompatible with the native constraints of quantum hardware, necessitating encoding strategies to map the original problem into a hardware-conformant form. While the classical overhead associated with such mappings is easily quantifiable and typically polynomial in problem size, it is much harder to quantify their overhead on the quantum algorithm, e.g., the transformation of the adiabatic timescale. …”
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Implementation of Chernobyl disaster optimizer based feature selection approach to predict software defects [version 2; peer review: 2 approved, 1 not approved] by Himansu Das, Ajay Kumar Jena, Kunal Anand

“…Feature selection (FS) selects the finest features while carefully discarding others. Several meta-heuristic algorithms, like Genetic Algorithm, Particle Swarm Optimization, Differential Evolution, and Ant Colony Optimization, have been used to develop defect prediction models. …”
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Insurance claims estimation and fraud detection with optimized deep learning techniques by P. Anand Kumar, S. Sountharrajan

“…The proposed work enhanced with Enhanced Hippopotamus Optimization Algorithm (EHOA) combined with a custom 12-layer CNN to optimize the hyperparameters and enhance the performance of the model. …”
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Optimal Computation Offloading Decisions Based on System Utility and Cost Balance by Bingxue Zhang, Xisheng Li, Jia You

“…Experiments conducted in a simulation based on the edge system of an industrial park verified that the cost-utility balanced optimization model achieves at least 7% reduction in the cost-utility ratio across varying user scales compared to traditional cost optimization models, while achieving over 20% reduction in optimization efficiency under different edge server scales. …”
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Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage by Aniket Basu, Hooman Oroojeni, Georgios Samakovitis, Mohammad Majid Al-Rifaie

“…The multi-drone-cell placement problem is solved using adapted Dispersive Flies Optimization alongside other meta-heuristic algorithms such as Particle Swarm Optimization and differential evolution. …”
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Optimizing Key Parameters of Ground Delay Program with Uncertain Airport Capacity by Jixin Liu, Kaijian Li, Minjia Yin, Xuehua Zhu, Ke Han

“…We also propose a joint GDP end-time-and-distance model solved with genetic algorithm. The optimization problem takes into account the GDP operational efficiency, airline and flight equity, and Air Traffic Control (ATC) risks. …”
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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…In this enhanced equilibrium optimizer (EEO), the Fisher score and accuracy score of the K-Nearest Neighbors (KNN) algorithm select the attributes optimally, whereas the synthetic minority oversampling technique combined with iterative partitioning filters (SMOTE-IPF) used to provide class balancing. …”
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Robust object counting through distribution uncertainty matching and optimal transport by Sabri Boughorbel, Fethi Jarray, Rachida Zegour, Nauman Ullah Gilal, Khaled Al Thelaya, Marco Agus, Jens Schneider

“…DUMLO formulates the loss function as a coupling between two optimal transport problems, which involves an unknown density map defined over the augmented points. …”
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Smart energy management for revenue optimization and grid independence in an Indian RDS by T. Yuvaraj, M. Thirumalai, M. Dharmalingam, Sudhakar Babu Thanikanti, Sanjeevikumar Padmanaban

“…The framework employs the hunter-prey optimization algorithm (HPOA) to enhance appliance scheduling, renewable energy integration (PV, WT, EV, BESS), and dynamic tariff management while addressing uncertainties in electric vehicle (EV) usage and renewable distributed generation (RDG) output. …”
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Optimization Scheduling of Multi-Regional Systems Considering Secondary Frequency Drop by Xiaodong Yang, Xiaotong Hua, Lun Cheng, Tao Wang, Yujing Su

“…The column and constraint generation algorithm is employed to solve this two-stage optimization problem. …”
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Collaborative optimal operation control of HVAC systems based on multi-agent by Chen Fu, Kaipeng Chen, Yan Xu, Dongyue Ming, Ruiwen Ye, Yingjun Wu, Lixia Sun

“…As a consequence, the computing efficiency of optimization algorithms is relatively low, posing challenges for real-time optimal operation control. …”
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Bayesian optimization of underground railway tunnels using a surrogate model by Hassan Liravi, Hoang-Giang Bui, Sakdirat Kaewunruen, Aires Colaço, Jelena Ninić

“…The results demonstrate that the proposed optimization framework, which combines the Bayesian optimization algorithm with surrogate models, effectively explores trade-offs among multiple design parameters. …”
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Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Bader Aldughayfiq, Hisham Allahem, Alshimaa Abdelraof Mahmoud, Wael Said, Hosameldeen Shabana, Mohamed Ezz

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Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…This paper seeks to elucidate the efficacy of deep learning models in medical diagnostics by employing concepts and strategies derived from biological system ontologies, such as genetic algorithms, particle swarm optimization, ant colony optimization, artificial immune systems, and swarm intelligence. …”
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Optimization of Shift Strategy Based on Vehicle Mass and Road Gradient Estimation by Huijun Yue, Haobo Jing, Zhenkun Dai, Jinyu Lin, Zihan Ma, Changtong Zhao, Pan Zhang

“…According to the estimation results, the existing shift strategy is optimized, and the software-in-the-loop simulation of the transmission controller is carried out to verify the function of the control algorithm software. …”
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Conveyor X-Ray Tomosynthesis Imaging With Optimized Structured Sequential Illumination by Xu Ma, Dong Wang, Angela Cuadros, Tianyi Mao, Qile Zhao, Gonzalo R. Arce, Tingfa Xu

“…Subsequently, a genetic algorithm is developed to optimize the exposure sequence of X-ray sources, and mask patterns, and during the dynamic measurement process. …”
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Low Complexity Optimized AOR Method for Massive MIMO Signal Detection by Muhammad Nauman Irshad, Muhamamd Muzamil Aslam, Rardchawadee Silapunt

“…To determine these parameters systematically, we incorporate an innovative approach using the Nelder-Mead Simplex optimization algorithm. This heuristic optimization technique allows us to find the optimal acceleration and relaxation parameters, thereby achieving superior detection accuracy with faster convergence for challenging system configurations. …”
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