Efficient Resource Allocation for Blockchain-Enabled Mobile Edge Computing: A Joint Optimization Approach by Moein Valitabar, Mohammad Fathi, Keivan Navaie

“…Leveraging these insights, we develop two low-complexity algorithms, which utilizes a greedy assignment strategy for MTs to ESs, and optimally allocates computational frequencies within the MEC and blockchain components. …”
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Optimization of Random Forest Algorithm with Backward Elimination Method in Classification of Academic Stress Levels by Salsabila Dani Amalia, Mula Agung Barata, Pelangi Eka Yuwita

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Optimizing Trade-Offs in Reliability, Security, and Freshness for Integrated Communication, Sensing, and Over-the-Air Computing by Tianyu Ren, Miao Zhang, Fangyu Wang, Kaiyuan Zheng

“…This paper addresses the trade-offs and optimization problems among reliability, security, and information freshness in integrated communication, sensing, and over-the-air computation (AirComp) systems. …”
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Impact of ISTA and FISTA iterative optimization algorithms on electrical impedance tomography image reconstruction by Nguyen Diep Quoc Tuan, Huynh Hoang Nhut, Ven Huynh Thanh, Cao Dinh Minh Quan, Tran Anh Tu, Tran Trung Nghia

“…It focuses on enhancing the convergence and accuracy of EIT image reconstruction by evaluating the effectiveness of these optimization algorithms when applied to regularized inverse problems, using standard regularization techniques. …”
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Benchmarking Metaheuristic Algorithms Against Optimization Techniques for Transportation Problem in Supply Chain Management by Felicia Lim Xin Ying, Suliadi Firdaus Sufahani

“…Metaheuristic algorithms, specifically Simulated Annealing (SA) and Particle Swarm Optimization (PSO), are implemented to explore alternative near-optimal solutions and assess the performance in terms of cost accuracy and computational efficiency. …”
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A Ｒeinforcement Learning of Cloud Ｒesource Scheduling Algorithm Based on Adaptive Weight by LI Cheng-yan, SUN Wei, TANG Li-min

“…We considered the cloud computing resource scheduling problem，and proposed a multi-objective optimization mathematical model to optimize task completion time and running cost simultaneously. …”
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Optimizing Electric Vehicle Routing Efficiency Using K-Means Clustering and Genetic Algorithms by Tal Gaon, Yovel Gabay, Miri Weiss Cohen

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Geometrical optimization of PWR spacer grids using GeN-Foam and Genetic Algorithms by Carlos Rodrigo Dias, Tiago Augusto Santiago Vieira, Andre Augusto Campagnole dos Santos, Graiciany de Paula Barros, Vitor Vasconcelos Araújo Silva, Ana Luiza Miranda Froes, Rebeca Cabral Gonçalves, Keferson de Almeida Carvalho, Higor Fabiano Pereira de Castro

“… This paper presents the results of Computational Fluid Dynamics (CFD) oriented geometrical optimization using the GeN-Foam solver applied to subchannels of the fuel assembly in a PWR-type nuclear reactor. …”
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New Ant Colony Optimization Algorithms for Variants of Multidimensional Assignments in d-Partite Graphs by Krzysztof Schiff

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Optimization of Combat Resource Allocation Based on Restricted Tournament Selection Social Genetic Algorithm by Shandong Yuan, Yun Ren, Han Zhou, Yongjing Cheng, Kai Yan

“…In addition, we innovatively incorporate the concept of ‘group effect’ from sociology, adding a socialization operator to the algorithm to accelerate convergence and improve the quality of optimal solutions. …”
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Boosting Malware Detection with AlexNet and Optimized Neural Networks Using the Grasshopper Algorithm by Mohammed Aswad

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A Genetic Algorithm based approach for designing multi-state computational grid with cost and bandwidth constraints by Debashreet Das, C.R. Tripathy, P.K. Tripathy, M.R. Kabat

“…This paper proposes a Genetic Algorithm (GA) based approach for optimization of reliability of computational grid with desired reliability under cost and bandwidth constraints. …”
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Exploring Virtual Machine Scheduling Algorithms: A Meta-Analysis by Salman Mahmood, Nor Adnan Yahaya

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An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions by Md.Al Imran Fahim, Md.Salah Uddin Yusuf, Monira Islam, Munshi Jawad Ibne Azad

“…To address these challenges, a new algorithm called horse herd optimization (HHO) has been applied to the maximum power point tracking (MPPT) controller. …”
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Efficient Task Scheduling in Cloud Computing: A Multiobjective Strategy Using Horse Herd–Squirrel Search Algorithm by V. Parthasaradi, A. Karunamurthy, C. H. Hussaian Basha, S. Senthilkumar

“…The objective is to provide an enhanced task scheduling algorithm for allocating the task of the user to different computing resources. …”
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A refined Greylag Goose optimization method for effective IoT service allocation in edge computing systems by Hossein Najafi Khosrowshahi, Hadi S. Aghdasi, Pedram Salehpour

“…We propose the Modified Greylag Goose Optimization (MGGO) algorithm, which introduces adaptive mechanisms for dynamic population partitioning, stagnation detection, and learning-based control. …”
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Optimizing Trajectories for Rechargeable Agricultural Robots in Greenhouse Climatic Sensing Using Deep Reinforcement Learning with Proximal Policy Optimization Algorithm by Ashraf Sharifi, Sara Migliorini, Davide Quaglia

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Cache Contention Aware Virtual Machine Placement and Mitigation Using Adaptive ABC Algorithm by Bharati Ainapure, Nishu Gupta, Mohammad Derawi

“…By optimizing the migration process with a focus on these critical factors, it ensures minimal computational overhead and optimal memory performance. …”
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Comparative analysis of software optimization methods in context of branch predication on GPUs by I. Yu. Sesin, R. G. Bolbakov

“…Covered approaches include: optimizing compilers, JIT-compilation, branch predictor, speculative execution, adaptive optimization, run-time algorithm specialization, profile-guided optimization. …”
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Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization by Eugenia Gutiérrez, Marianela Noriega, Cecilia Fernández, Nadia Pantano, Leandro Rodriguez, Gustavo Scaglia

“…The proposed technique employs Legendre polynomials to parameterize two control actions (the feeding rates of glucose and xylose), and it uses a hybrid optimization algorithm combining Monte Carlo sampling with genetic algorithms for coefficient selection. …”
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