Optimizing airway network efficiency with the A-star algorithm: a case study of Ho Chi Minh FIR by Ngoc Hoang Quan Nguyen, Thi Hoai An Vu, Hoang Mai Le, Mai Phuong Nguyen, Thi Thu Tra Le, Thi Thuy Trang Nguyen, Ngoc Nhu Y Nguyen

“…To address these challenges, this study proposes optimizing the airway network in 2D space using the A-star algorithm, tailored for the HCM FIR. …”
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Implementing a novel TOPSIS-sine cosine algorithm-based hybrid optimization in machining medium-hardened steel by Ramanuj Kumar, Mohammad Rafighi, Oğur İynen, M. Prem Kumar Reddy, Shrikant Zade, Mustafa Özdemir, Anish Pandey, Ramanpreet Singh

“…This research recommended insert type-3 at optimized cutting conditions to improve machinability and sustainability in turning medium-hard AISI 4340 grade steel.…”
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A Modified Sine Cosine Algorithm Based on A Novel Locally Weighted Method for Global Optimization Problems by Shahad Mohammed, Nazar Hussein, Mohammed Alkahya

“…According to the experimental data gathered, the LWSCA's convergence, exploration, and exploitation tendencies have all greatly improved. According to the results, the suggested LWSCA method is a good one that performs better than SCA and other rival algorithms in most functions.…”
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Diagnosing schizophrenia with routine blood tests: a comparative analysis of machine learning algorithms by Yavuz Selim Ogur, Ayse Erdogan Kaya, Nur Banu Ogur, Beyza Erdogan Akturk

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Optimizing SVC placement for enhanced voltage stability using a novel index and hybrid ABC-PSO algorithm by Hafizur Rahman, Roman Mia, Mustafizur Rahman, Md. Faiyaj Ahmed Limon, Md. Shahid Iqbal, Md. Fahad Jubayer, Md. Rabiul Karim, Md. Janibul Alam Soeb

“…The ABC-PSO hybrid algorithm converges very quickly to optimal solutions in 10 to 40 iterations and outperforms five state-of-the-art optimizers with a 100 % success rate for the IEEE 14-bus system and a mean computation time of 0.041 s per iteration. …”
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Recent advancements in stereolithography (SLA) and their optimization of process parameters for sustainable manufacturing by Asmaul Husna, Salahuddin Ashrafi, ANM Amanullah Tomal, Noshin Tasnim Tuli, Adib Bin Rashid

“…Most of the research has focused on current improvements, but there is a need for more attention to future work.…”
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An optimized method for short-term load forecasting based on feature fusion and ConvLSTM-3D neural network by Xiaofeng Yang, Shousheng Zhao, Kangyi Li, Wenjin Chen, Si Zhang, Jingwei Chen

“…As renewable energy continues to penetrate modern power systems, accurate short-term load forecasting is crucial for optimizing power generation resource allocation and reducing operational costs. …”
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Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms by Sawsan Akram Hassan, Mahir M. Hason, Ammar N. Hanoon, Ali A. Abdulhameed

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A multi-population multi-objective maritime inventory routing optimization algorithm with three-level dynamic encoding by Tianyu Liu, Jiaping Liu, He Xu

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ML-based approach to potato diseases diagnosis using image processing and whale optimization algorithm for feature selection by Zhongxu Li, Seyed Mohamad Javidan

“…Nature-inspired feature extraction techniques, such as the Whale Optimization Algorithm (WOA), have gained considerable attention recently. …”
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S-EPSO: A Socio-Emotional Particle Swarm Optimization Algorithm for Multimodal Search in Low-Dimensional Engineering Applications by Raynald Guilbault

“…S-EPSO performed best with the most challenging 5D functions of the benchmark. These results clearly illustrate the potential of S-EPSO when it comes to dealing with practical engineering optimization problems limited to five dimensions.…”
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Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

“…This study introduces a hybrid AI-based optimization framework to enhance climbing perch aquaculture in smart farming systems, targeting improvements in both productivity and cost-efficiency. …”
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Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data by Zihan Zhou, Yanhong Guo, Yitao Wang, Jingfan Lyu, Haoran Gong, Xin Ye, Yachao Li

“…Our research integrates a priori knowledge of threat zone locations, speeds, and directions with real-time data on the UAVs position relative to the threat zones to effectively manage dynamic threat zones, allowing UAVs to dynamically decide whether to navigate around or through these zones, thus significantly reducing trajectory costs. To further improve search efficiency and solution quality, strategies such as greedy initialization and K-means clustering are incorporated, enhancing the algorithms multi-objective optimization capabilities. …”
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Advanced AI approaches for the modeling and optimization of microgrid energy systems by Mohammed Amine Hoummadi, Badre Bossoufi, Mohammed Karim, Ahmed Althobaiti, Thamer A. H. Alghamdi, Mohammed Alenezi

“…Three AI techniques, Genetic Algorithm (GA), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO), are employed to optimize the optimal composition of energy sources based on solar energy and wind energy, battery storage, and load profiles. …”
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Multi-objective multi-workflow task offloading based on evolutionary optimization by Teliekebieke Misha, Lisheng Sun, Zheng-yi Chai

“…We propose an improved decomposition-based multi-objective evolutionary algorithm (MOEA/D) incorporating two novel strategies: (1) population initialization based on prior knowledge, and (2) a population distribution-based weight adjustment scheme. …”
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ATHOS: A Hybrid Accelerator for PQC CRYSTALS-Algorithms Exploiting New CV-X-IF Interface by Alessandra Dolmeta, Maurizio Martina, Guido Masera

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A Chaotic Decomposition-Based Approach for Enhanced Multi-Objective Optimization by Javad Alikhani Koupaei, Mohammad Javad Ebadi

“…To address these issues, this paper proposes a chaotic decomposition-based approach that leverages the ergodic properties of chaotic maps to enhance optimization performance. The proposed method consists of three key stages: (1) chaotic sequence initialization, which generates a diverse population to enhance the global search while reducing computational costs; (2) chaos-based correction, which integrates a three-point operator (TPO) and a local improvement operator (LIO) to refine the Pareto front and balance the exploration–exploitation trade-offs; and (3) Tchebycheff decomposition-based updating, ensuring efficient convergence toward optimal solutions. …”
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Enhanced multi-level K-means clustering and cluster head selection using a modernized pufferfish optimization algorithm for lifetime maximization in wireless sensor networks by Anjana Koyalil, Sivacoumar Rajalingam

“…This optimization enhances the network coverage, data acquisition efficiency, and energy conservation, ultimately prolonging the network lifetime and improving overall system reliability. …”
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Smart building energy management with renewables and storage systems using a modified weighted mean of vectors algorithm by Mohamed Ebeed, Sabreen hassan, Salah Kamel, Loai Nasrat, Ali Wagdy Mohamed, Abdel-Raheem Youssef

“…Results indicate that MINFO significantly improves smart building EM, achieving a reduction of 53.20% in electricity costs (cost only), 53.19% in PAR (PAR only), and 50.84% in combined cost and PAR compared to the base case. …”
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Research on Multi-objective Shielding Intelligent Optimization Method Based on Non-dominated Sorting Genetic Algorithm NSGA-Ⅲ by WANG Mengqi, ZHENG Zheng, MEI Qiliang, PENG Chao, GAO Jing, ZHOU Yan

“…This study is dedicated to exploring an advanced intelligent multi-objective shielding optimization method based on the third generation non-dominated sorting genetic algorithm (NSGA-Ⅲ). …”