Evolutionary Algorithms for Edge Server Placement in Vehicular Edge Computing by A. Surayya, Md Muzakkir Hussain, V. Dinesh Reddy, Ashu Abdul, Firoj Gazi

“…These include the Genetic Algorithm (GA), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Teaching-Learning-Based Optimization (TLBO). …”
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Integration of Distributed Energy Resources in Unbalanced Networks Using a Generalized Normal Distribution Optimizer by Laura Sofía Avellaneda-Gómez, Brandon Cortés-Caicedo, Oscar Danilo Montoya, Jesús M. López-Lezama

“…A leader–followeroptimization framework is adopted, where the leader stage utilizes the Generalized Normal Distribution Optimization (GNDO) algorithm to generate candidate solutions, while the follower stage conducts power flow calculations through successive approximation to assess the objective value. …”
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Flexible Demand Side Management in Smart Cities: Integrating Diverse User Profiles and Multiple Objectives by Nuno Souza e Silva, Paulo Ferrão

“…Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. …”
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Evolutionary Algorithms and Quantum Computing: Recent Advances, Opportunities, and Challenges by Junaid Ur Rehman, Muhammad Shohibul Ulum, Abdurrahman Wachid Shaffar, Amirul Adlil Hakim, Mujirin, Zaid Abdullah, Hayder Al-Hraishawi, Symeon Chatzinotas, Hyundong Shin

“…Nature-inspired metaheuristics have emerged as promising candidates for fulfilling this optimization role. In this paper, we discuss both of these potential directions at the intersection of evolutionary computing and quantum computing while surveying some of the most promising advancements in these directions. …”
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Decision-Making Model for Life Cycle Management of Aircraft Components by Igor Kabashkin, Vitaly Susanin

“…The optimization method on the base of genetic algorithm (GA) is employed to minimize total life cycle costs while maintaining component reliability within acceptable thresholds. …”
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Fair Resource Allocation Algorithm for OFDMA System with Imperfect CSI by Yaohui Wu, Youming Li, Liping Jin, Pengfei Shao

“…In order to solve this problem, a fair resource allocation algorithm was proposed to maximize the system ergodic capacity, while the fairness could be adjusted flexibly by introducing the fairness relaxation factor. …”
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Fair Resource Allocation Algorithm for OFDMA System with Imperfect CSI by Yaohui Wu, Youming Li, Liping Jin, Pengfei Shao

“…In order to solve this problem, a fair resource allocation algorithm was proposed to maximize the system ergodic capacity, while the fairness could be adjusted flexibly by introducing the fairness relaxation factor. …”
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Algorithms to reconstruct past indels: The deletion-only parsimony problem. by Jordan Moutet, Eric Rivals, Fabio Pardi

“…When sequences can only undergo substitutions, optimal reconstructions can be efficiently computed using well-known algorithms. …”
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Topology Knapsack Problem for Geometry Optimization by Hsiao-Hui Li, Po-Chun Chang, Yuan-Hsun Liao

“…While several variants have been developed, including the 0/1, fractional, and multi-dimensional knapsack problems, no existing model simultaneously optimizes multiple attributes like rarity, importance, and preference alongside the weight and volume of items. …”
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Deep learning algorithms for detecting fractured instruments in root canals by Ekin Deniz Çatmabacak, İrem Çetinkaya

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An Efficient Evolutionary Neural Architecture Search Algorithm Without Training by Yang An, Changsheng Zhang, Jintao Shao, Yuxiao Yan, Baiqing Sun

“…By making full use of the information carried by individuals, we promoted information exchange and optimization between individuals and their neighbors, thereby improving local search capabilities while maintaining global search capabilities. …”
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Improved Field Obstacle Detection Algorithm Based on YOLOv8 by Xinying Zhou, Wenming Chen, Xinhua Wei

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Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem by Jin Qin, Ling-lin Ni, Feng Shi

“…The method is a two-layer algorithm, in which the external subalgorithm optimizes the decision of the facility location decision while the internal subalgorithm optimizes the decision of the allocation of customer's demand under the determined location decision. …”
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Human Activity Recognition Using Graph Structures and Deep Neural Networks by Abed Al Raoof K. Bsoul

“…To address this, we applied the Firefly Optimization Algorithm to fine-tune the hyperparameters of both the graph-based model and a CNN baseline for comparison. …”
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Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field by YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun

“…The prediction accuracy of the BP neural network optimized by particle swarm optimization is slightly better than that of the BP neural network optimized by genetic algorithm.…”
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Advancing Pile-Bearing Capacity Prediction with Meta-Heuristic Enhanced Specific ANFIS strategys by Zhongmiao Dang

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Advances in Digital Signature Algorithms: Performance, Security and Future Prospects by Lyu Shuhan

“…The results show that while optimizations improve computational efficiency, challenges persist, especially with potential quantum threats that could undermine these algorithms' security. …”
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Advanced Design of Naval Ship Propulsion Systems Utilizing Battery-Diesel Generator Hybrid Electric Propulsion Systems by Youngnam Park, Heemoon Kim

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Improving Genetic Algorithm with Fine-Tuned Crossover and Scaled Architecture by Ajay Shrestha, Ausif Mahmood

“…Genetic Algorithm (GA) is a metaheuristic used in solving combinatorial optimization problems. …”
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Personalization of AI-Based Digital Twins to Optimize Adaptation in Industrial Design and Manufacturing—Review by Izabela Rojek, Dariusz Mikołajewski, Ewa Dostatni, Jan Cybulski, Mirosław Kozielski

“…The key findings highlight the growing emphasis on scalable model architectures, multimodal data integration, and the use of high-performance computing platforms. While existing research has focused on model decomposition, structural optimization, and algorithmic integration, there remains a need for fast DT platforms that support diverse user requirements. …”
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