Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…Specifically, the VAE-based approach reduces total travel costs by an average of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>8</mn><mo>%</mo></mrow></semantics></math></inline-formula> and improves customer priority satisfaction by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>95</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared to traditional hyperheuristic methods. …”
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Interference Minimization in Beyond-Diagonal RIS-Assisted MIMO Interference Channels by Ignacio Santamaria, Mohammad Soleymani, Eduard Jorswieck, Jesus Gutierrez

“…In the first stage, the passive BD-RIS is designed to minimize the aggregate interference power at all receivers, a cost function called interference leakage (IL). To this end, we propose an optimization algorithm in the manifold of unitary matrices and a suboptimal but computationally efficient solution. …”
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Method and experimental verification of spatial attitude prediction for an advanced hydraulic support system under mining influence by Zhuang Yin, Kun Zhang, ZengBao Zhang, Hongyue Chen, Lingyu Meng, Zhen Wang, Mingchao Du, Xiangpeng Hu, Defu Zhao, Dan Tian

“…Based on this, the WOA algorithm was utilized to search for the optimal number of neurons in the hidden layer and the learning rate. …”
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Human resource management model based on multi-objective differential evolution and multi-skill scheduling by Yanxia Dong, Tiantian Lu

“…The experimental results show that compared to the single skill model, this model can effectively shorten project duration, reduce human resource costs, and improve skill scores. For example, in a specific experimental dataset, when the project duration is limited to 200 h, the most suitable labor duration for the plan is 193.8 h, the human resource cost is 7493 yuan, and the skill score is improved by 268. …”
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Research on an Intelligent Design Method for the Geometric Structure of Three-Layer Hollow Fan Blades by Jialin Lei, Jiale Chao, Chuipin Kong, Xionghui Zhou

“…The geometric structure design of three-layer hollow fan blades is extremely complex, which is not only directly related to the blade quality and manufacturing cost but also has a significant impact on engine performance. …”
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Analysis of the impact of mobile robots on the efficiency of warehousing and transport processes in modern textile manufacturing by Karabegović Isak

“…Studies indicate that the deployment of AMR technology can improve warehouse efficiency by up to 40% and reduce operational costs by as much as 25%, while also decreasing human error and enhancing workplace safety. …”
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Addressing the Return Visit Challenge in Autonomous Flying Ad Hoc Networks Linked to a Central Station by Ercan Erkalkan, Vedat Topuz, Ali Buldu

“…This paper presents different approaches to efficiently directing UAVs and explains how heuristic algorithms can enhance our understanding and improve current methods for task assignments.…”
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Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and a distribution static compensator (DSTATCOM), to assess their long-term techno–economic and environmental impacts. The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. …”
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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…These methods have high computational costs and are not efficient for real-time applications.MethodsTo address these issues, this paper presents a Quantum-behaved Particle Swarm Optimization model enhanced by deep reinforcement learning (RL-QPSO Net) aimed at improving global optimality and adaptability in path planning. …”
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A Quantum-like Approach to Semantic Text Classification by Anastasia S. Gruzdeva, Rodion N. Iurev, Igor A. Bessmertny, Andrei Y. Khrennikov, Alexander P. Alodjants

“…We also explore methods for reducing the computational cost of algorithms based on the wave model of text representation. …”
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State-of-the-Art Fault Detection and Diagnosis in Power Transformers: A Review of Machine Learning and Hybrid Methods by Lebo Dina Mashifane, Bongumsa Mendu, Bessie Baakanyang Monchusi

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LSTM-ANN-GA A HYBRID DEEP LEARNING MODEL FOR PREDICTIVE MAINTENANCE OF INDUSTRIAL EQUIPEMENT by Farouk Noumich, Abouchabaka Jaafar, Amrani Ayoub

“…Predictive maintenance is essential for ensuring the reliability of industrial equipment and minimizing maintenance costs. However, current predictive algorithms sometimes reach their limits in terms of accuracy, necessitating continuous improvement. …”
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Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

“…The primary objective of this system is to efficiently classify and analyze social media content related to Hajj and Umrah services. To improve the effectiveness of this classification model, we introduce a predictive optimization strategy that employs a deep neural network as the learning module and utilizes particle swarm optimization to refine the weighting parameters. …”
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Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks by Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He

“…Finally, the particle swarm optimization algorithm is used for hyperparameter optimization to improve the prediction accuracy. …”
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Enhancing energy efficiency of industrial boiler application by the integration of ground-source heat pumps and photovoltaic-thermal solar water collectors by Praveen Barmavatu, Baburao Gaddala, Sharun Mendonca, Sonali Anant Deshmukh, Marco Rosales-Vera, Hussein Togun, Ramalinga Viswanathan Mangalaraja, Vineet Singh Sikarwar

“…Significant reductions were observed in annual heating loads and grid-purchased electricity compared to traditional systems. Optimization was achieved using a hybrid approach that combined Genetic Algorithms (GA) and machine learning (ML) techniques, which iteratively improved system design and operational strategies. …”
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Enhanced Multi-Model Deep Learning for Rapid and Precise Diagnosis of Pulmonary Diseases Using Chest X-Ray Imaging by Rahul Kumar, Cheng-Tang Pan, Yi-Min Lin, Shiue Yow-Ling, Ting-Sheng Chung, Uyanahewa Gamage Shashini Janesha

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Navigating Intelligence: A Survey of Google OR‐Tools and Machine Learning for Global Path Planning in Autonomous Vehicles by Alexandre Benoit, Pedram Asef

“…This problem is central to enhancing ROMIE's operational efficiency and competitiveness against human labor by optimizing cost and time. The primary aim of this research is to advance GPP by developing, evaluating, and improving a cost‐efficient software and web application. …”
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Residential Energy Management Method Based on the Proposed A3C-FER by Jinjiang Zhang, Qiang Lin, Lu Wang, Orefo Victor Arinze, Zihan Hu, Yantai Huang

“…In comparison with the Proximal Policy Optimization (PPO) and Deep Q-Network (DQN) algorithms, the novel approach not only improves the average reward value post-convergence by 38.48% and 47.17%, respectively, but also significantly reduces the training duration by 81.19% within a multi-threaded computational environment.…”
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SLPDBO-BP: an efficient valuation model for data asset value by Cuiping Zhou, Shaobo Li, Cankun Xie, Panliang Yuan, Zihao Liao

“…Secondly, in an attempt to comprehensively evaluate the optimization performance of SLPDBO, a series of numerical optimization experiments are carried out with 20 test functions and with popular optimization algorithms and dung beetle optimizer (DBO) algorithms with different improvement strategies. …”
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The Design, Creation, Implementation, and Study of a New Dataset Suitable for Non-Intrusive Load Monitoring by Carlos Rodriguez-Navarro, Francisco Portillo, Francisco G. Montoya, Alfredo Alcayde

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