A Novel Hybrid Metaheuristic MPA-PSO to Optimize the Properties of Viscous Dampers by Elmira Shemshaki, Mohammad Hasan Haddad, Mohammadreza Mashayekhi, Seyyed Meisam Aghajanzadeh, Ali Majdi, Ehsan Noroozinejad Farsangi

“…Furthermore, in the more complex five-story frame, the two comparison methods were unable to reach the optimal solution, while the proposed method successfully found an optimal solution. …”
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Allocating the Sample Size in Phase II and III Trials to Optimize Success Probability by Daniele De Martini

“…The overall success probability (OSP) is accounted for.</p><p>{\bf Methods} Focus is placed on the amount of resources that should be provided to phase II and III trials to attain a good level of OSP, and on how many of these resources should be allocated to phase II to optimize OSP. …”
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Enhancing curve smoothness with whale optimization algorithm in positivity and monotonicity-preserving interpolation by Salwa Syazwani Mahzir, Md Yushalify Misro

“…This study integrated a metaheuristic optimization method, specifically the whale optimization algorithm (WOA), to enhance the positivity and monotonicity-preserving interpolation methods by optimizing the free shape parameter. …”
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Optimal scheduling of BIES with multi-energy flow coupling based on deep RL by XIA Xuhua, YANG Jiandi, SHI Yongtao

“…Building integrated energy systems （BIESs） can enhance energy efficiency ratio （EER） and reduce carbon emissions while meeting diverse user-side load demands. To further improve the energy dispatch capability of BIES， this paper proposes a low-carbon economic and optimal dispatch method for BIES with multi-energy flow coupling based on deep reinforcement learning （deep RL）. …”
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Machine Learning-Driven Prediction of Vitamin D Deficiency Severity with Hybrid Optimization by Usharani Bhimavarapu, Gopi Battineni, Nalini Chintalapudi

“…Incorporating advanced optimization techniques, the proposed method’s promise for generating accurate predictions is highlighted in the study.…”
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Low-Frequency Square Kilometer Array Pattern Optimization via Convex Programming by Giada Maria Battaglia, Giuseppe Caruso, Pietro Bolli, Maria Grazia Labate, Roberta Palmeri, Andrea Francesco Morabito

“…The proposed method minimizes the peak sidelobe level while ensuring full control of the receiving pattern across the entire angular domain. …”
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Multi-objective layout optimization of hospital outpatient clinics based on NSGA II by Yanlin Zhao, Jiamei Gu

“…The results show that the new plan reduces patient walking distance by 57.2%, shortens waiting time by 59%, and enhances medical staff collaboration efficiency, while only increasing costs by 5.6%. This demonstrates the effectiveness and feasibility of the improved NSGA-II method in handling complex multi-objective optimization problems for outpatient layouts. …”
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Decentralized Multi-Robot Navigation Based on Deep Reinforcement Learning and Trajectory Optimization by Yifei Bi, Jianing Luo, Jiwei Zhu, Junxiu Liu, Wei Li

“…Additionally, it introduces safety constraints through an artificial potential field (APF) to optimize these trajectories. Additionally, a constrained nonlinear optimization method further refines the APF-adjusted paths, resulting in the development of the GNN-RL-APF-Lagrangian algorithm. …”
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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…Specifically, we propose an optimization algorithm based on Differential Evolution (DE) that adjusts anchor scales and ratios while determining the most appropriate number of these parameters for each dataset based on the annotated data. …”
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Optimizing Inventory Costs in Manufacturing Systems Using Trapezoidal and Pentagonal Fuzzy Numbers by Prasantha Bharathi Dhandapani, Kalaiarasi Kalaichelvan, Soundaria Ramalingam, Mohamed Biomy, Taha Radwan

“…In the suggested model, the graded mean integration representation method is used to describe defuzzification while trapezoidal and pentagonal fuzzy numbers are used to calculate the optimal cost though there are different types of fuzzy numbers available that are used to test the optimality. …”
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Optimization of High-Performance Computing Job Scheduling Based on Offline Reinforcement Learning by Shihao Li, Wei Dai, Yongyan Chen, Bo Liang

“…In large-scale, distributed high-performance computing systems, the increasing complexity of job scheduling has expanded along with the growth of computational resources and job diversity. While heuristic scheduling strategies with various optimization objectives have shown promising results, their effectiveness is often limited in real-world applications due to the dynamic nature of workloads and system configurations. …”
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Coverage Optimization Algorithm Based on Sampling for 3D Underwater Sensor Networks by Du Xiaoyu, Sun Lijuan, Liu Linfeng

“…First, the coverage problem in 3D space is converted into a 2D plane for heterogeneous networks via sampling plane in the target 3D space. Second, the optimization in the 2D plane is converted into an optimization in a line segment by using the line sampling method in the sample plane. …”
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EFFICACY OF OPTIMIZED REMINERALIZING THERAPY IN POST-COVID-19 PATIENTS: EVALUATION OF RESULTS by N.M. Savielieva, M.E. Diasamidze

“…Objective: to evaluate the effectiveness of the optimized method of remineralization by studying the dynamics of dental parameters in patients after 6 and 12 months. …”
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Enhanced Wavelet-Based Medical Image Denoising with Bayesian-Optimized Bilateral Filtering by Mehdi Taassori

“…In this paper, we present an enhanced wavelet-based method for medical image denoising, aiming to effectively remove noise while preserving critical image details. …”
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Genetic Algorithms Applied to Optimize Neural Network Training in Reference Evapotranspiration Estimation by Eluã Ramos Coutinho, Jonni G.F. Madeira, Robson Mariano da Silva, Angel Ramon Sanchez Delgado, Alvaro L.G.A. Coutinho

“…These findings suggest the results generated achieve an precision between 92.91% and 97.51% in comparison to the Penman-Monteith method. This confirms that employing Genetic Algorithms (GA) to automate the training and optimization of the model is effective and enhances the neural network's capacity to predict ETo.…”
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De-speckling of medical ultrasound image using metric-optimized knowledge distillation by Mostafa Khalifa, Hanaa M. Hamza, Khalid M. Hosny

“…This noise varies with image intensity, which limits the effectiveness of traditional denoising methods. We introduce the Metric-Optimized Knowledge Distillation (MK) model, a deep-learning approach that utilizes Knowledge Distillation (KD) for denoising ultrasound images. …”
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Optimization of sludge recirculation for sustainable water treatment at Ait Massoud dam Morocco by Radouane El Amri, Rajaa Zahnoune, Otmane Boudouch, Reda Elkacmi

“…A techno-economic analysis revealed that applying this method on the scale of the plant (6 000 m3/h) would result in daily savings of around 3,715 euros, while reducing the disposal of almost 7,200 m3/day of sludge, thus helping to reduce the environmental footprint. …”
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DRCO: Dense-Label Refinement and Cross Optimization for Semi-Supervised Object Detection by Yunlong Qin, Yanjun Li, Feifan Ji, Yan Liu, Yu Wang, Ji Xiang

“…In semi-supervised object detection (SSOD), the methods based on dense pseudo-labeling bypass complex post-processing while maintaining competitive performance compared to the methods based on sparse pseudo-labeling. …”
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Localization Algorithm in Wireless Sensor Networks Based on Multiobjective Particle Swarm Optimization by Ziwen Sun, Li Tao, Xinyu Wang, Zhiping Zhou

“…The simulation results show considerable improvements in terms of localization accuracy and convergence rate while keeping a limited archive size by a method using the global optimal selection operator and dynamically maintaining the archive.…”
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Optimization of bike-sharing repositioning operations: A reactive real-time approach by Enrique Jiménez-Meroño, Francesc Soriguera

“…One of the critical issues in the operation of vehicle-sharing systems is the optimization of the fleet repositioning movements. Repositioning implies the artificial movement of vehicles from places where they accumulate to others in which they are scarce. …”
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