Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…This study focuses on the multi-objective coordination problem in university campus planning and design, proposing an optimized methodology integrating an improved multi-objective decision-making framework. …”
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Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling by Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi

“…Simulation analysis demonstrates that the new method can decrease energy consumption and average delay much lower than Round-Robin and threshold-based algorithms. The feature of temperature adaptation within Boltzmann further guarantees the achievement of the optimal scheduling actions while ensuring flexibility in the case or altering load percentages. …”
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Optimizing Neural Recording Front-Ends Toward Enhanced Spike Sorting Accuracy in High-Channel-Count Systems by Yunzhu Chen, Xiaolin Yang, Georges Gielen, Carolina Mora Lopez

“…This study explores how design choices in amplifiers, filters, and analog-to-digital converters (ADCs) affect the accuracy of well-established spike sorting algorithms. Our primary objective is to identify the minimal requirements that ensure high sorting accuracy while facilitating power- and area-efficient analog front-ends, which is especially needed for multi-channel recording-only applications. …”
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High-Radix Taylor-Optimized Tone Mapping Processor for Adaptive 4K HDR Video at 30 FPS by Xianglong Wang, Zhiyong Lai, Lei Chen, Fengwei An

“…By integrating an exposure-adaptive factor into a bilateral filtering framework, we dynamically optimize parameters to achieve consistent performance across fluctuating illumination conditions. …”
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Enhancing Security for Resource-Constrained Smart Cities IoT Applications: Optimizing Cryptographic Techniques with Effective Field Multipliers by Atef Ibrahim, Fayez Gebali

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Optimal off-grid electricity supply for a residential complex using water-energy-economic-environmental nexus by Mozhgan Jafari, Hoseyn Sayyaadi

“…A multi-objective optimization framework was applied, using Genetic Algorithms alongside TOPSIS and AHP decision-making methods, considering the Water-Energy-Economic-Environmental (WEEE) Nexus. …”
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Optimizing deep learning for accurate blood cell classification: A study on stain normalization and fine-tuning techniques by Mohammed Tareq Mutar, Jaffar Nouri Alalsaidissa, Mustafa Majid Hameed, Ali Almothaffar

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DRBO—A Regional Scale Simulator Calibration Framework Based on Day-to-Day Dynamic Routing and Bayesian Optimization by Xuan Jiang, Yibo Zhao, Chonghe Jiang, Junzhe Cao, Alexander Skabardonis, Alex Kurzhanskiy, Raja Sengupta

“…Based on the decomposition, the DRBO framework uses iterative algorithms to find the best dynamic combinations. It utilizes the Bayesian optimization and day-to-day routing update to separately calibrate the dynamic, then combine them sequentially in an iterative way. …”
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Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
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Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

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Advancing mmWave Altimetry for Unmanned Aerial Systems: A Signal Processing Framework for Optimized Waveform Design by Maaz Ali Awan, Yaser Dalveren, Ali Kara, Mohammad Derawi

“…This article addresses challenges arising from radial velocity due to UAS descent rates and terrain variation through theoretical and mathematical approaches for characterization and mandatory compensation. While constant false alarm rate (CFAR) algorithms have been reported for ground detection, a comparison of their variants within the scope UAS altimetry is limited. …”
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Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…This work points out the possibility of taking complete advantage of advanced machine learning algorithms along with metaheuristics optimization in improving photocatalytic processes, hence opening a bright avenue for real applications in water treatment.…”
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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
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Nonlinear Narrowband Active Noise Control for Tractors Based on a Momentum-Enhanced Volterra Filter by Tao Zhang, Zhixuan Guan, Shuai Zhang, Kai Song, Boyan Huang

“…The proposed approach integrates the nonlinear representation power of the Volterra filter with a momentum optimization mechanism to enhance convergence speed while maintaining robust steady-state accuracy. …”
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Network- and Demand-Driven Initialization Strategy for Enhanced Heuristic in Uncapacitated Facility Location Problem by Jayson Lin, Shuo Yang, Kai Huang, Kun Wang, Sunghoon Jang

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Study on Trajectory Planning for Polishing Free-Form Surfaces of XY-3-RPS Hybrid Robot by Xiaozong Song, Junfeng An, Xingwu Ma

“…Additionally, a hybrid optimization framework combining a genetic algorithm (GA) and local search (LS) is proposed to address the challenges of balancing global optimization with local fine-tuning in traditional trajectory planning methods. …”
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Two-Stage Uncertain UAV Combat Mission Assignment Problem Based on Uncertainty Theory by Haitao Zhong, Rennong Yang, Aoyu Zheng, Mingfa Zheng, Yu Mei

“…A modified particle swarm optimization (PSO) algorithm is designed to solve the ETUCMA model to get the expected value-effective solution of the TUCMA model. …”
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Minimization of total costs for distribution systems with battery energy storage systems and renewable energy sources by Thai Dinh Pham, Thang Trung Nguyen, Le Chi Kien

“…Besides, this work also suggests an open-source simulator (OpenDSS) for addressing the power flow problem and develops a co-simulation between two active software (OpenDSS and MATLAB) through the component object model (COM) interface for addressing the continuous optimization problems. The proposed solution by MCOA has demonstrated superiority over other methods through total cost savings of up to 24.13% and 27.46% in IEEE 123-bus UDS and 55-bus BDS, while the values are only 23.11% and 26.50% for salp swarm algorithm (SSA) and 23.76% and 26.78% for coyote optimization algorithm (COA), respectively, as compared to the original cases. …”
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Revolutionizing RPAS logistics and reducing CO2 emissions with advanced RPAS technology for delivery systems by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte, Richard C. Millar, Robert Walter Meyer

“…These integrations significantly decrease battery consumption in Remotely Piloted Aircraft Systems (RPAS) and lower transportation costs, while also optimizing delivery times, reducing operational risks, and minimizing CO2 emissions. …”
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