An Overview and Comparison of Traditional Motion Planning Based on Rapidly Exploring Random Trees by Yang Chu, Quanlin Chen, Xuefeng Yan

“…Motion planning is a fundamental problem in robotics that involves determining feasible or optimal paths within finite time. While complete motion planning algorithms are guaranteed to converge to a path solution in finite time, they are proven to be computationally inefficient, making them unsuitable for most practical problems. …”
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Evaluating energy efficiency in Turkish electric distribution using network DEA and GA models by Serpil Aydin, Talat Şenel

“…This shows that Sakarya EDC operates optimally and is a benchmark for other companies in the sector. …”
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Impact of integrating type-1 distributed generation on distribution network using modified genetic algorithm and voltage stability index: a technical and cost–benefit analysis appr... by Olakunle Elijah Olabode, Daniel Oluwaseun Akinyele, Titus Oluwasuji Ajewole, Samuel Okeolu Omogoye, Akeem Abimbola Raji

“…The backward-forward sweep formed the backbone of the load flow, while the voltage stability index was used to select the suitable buses where type-1 DG was integrated for optimal performance. …”
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Electric Vehicle Routing Problem with Heterogeneous Energy Replenishment Infrastructures Under Capacity Constraints by Bowen Song, Rui Xu

“…Extensive numerical experiments demonstrate HACO’s effective integration of problem-specific characteristics. The algorithm resolves charging conflicts via dynamic rescheduling while optimizing charging-battery swapping decisions under an on-demand energy replenishment strategy, achieving global cost minimization. …”
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Comprehensive improvement of energy efficiency and indoor environmental quality for university library atrium—A multi-objective fast optimization framework by Shen Xu, Yongzhong Chen, Jianlin Liu, Jian Kang, JinFeng Gao, Yuchen Qin, Wenjun Tan, Gaomei Li

“…Finally, a multi-objective fast optimization framework coupled with machine learning algorithms was used to achieve the optimal design of university library atrium. …”
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Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis by Yi Xu, Ying Mao, Xiaoting Hua, Yan Jiang, Yi Zou, Zhichao Wang, Zubi Liu, Hongrui Zhang, Lingling Lu, Yunsong Yu

“…By constructing training and test datasets on all SNPs, intersected SNPs, and randomly generated SNPs, we developed a Machine learning (ML) framework using twelve different algorithms. Then, we compared the performances of the various ML models and used the SHapley Additive exPlanations (SHAP) framework to decipher why and how decisions are made within the optimal algorithm. …”
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Innovative Business Models Towards Sustainable Energy Development: Assessing Benefits, Risks, and Optimal Approaches of Blockchain Exploitation in the Energy Transition by Aikaterini Papapostolou, Ioanna Andreoulaki, Filippos Anagnostopoulos, Sokratis Divolis, Harris Niavis, Sokratis Vavilis, Vangelis Marinakis

“…Blockchain has the potential to change energy services towards this direction. To optimally exploit blockchain, innovative business models need to be designed, identifying the opportunities emerging from unmet needs, while also considering potential risks so as to take action to overcome them. …”
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Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City) by Tharisa Melani, Sobri Abusini, Marjono Marjono

“…These findings highlight the effectiveness of combining these algorithms in fuel distribution optimization, providing a more efficient solution compared to existing routes. …”
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Micro hole drilling and multi criteria optimization of soda lime glass via ultrasonic assisted rotary electrochemical discharge drilling by Sahil Grover, Viveksheel Rajput, Sanjay Kumar Mangal, Sarbjit Singh, Sandeep Singh, Shubham Sharma, Ehab El Sayed Massoud, Dražan Kozak, Jasmina Lozanovic

“…The present article optimizes the ultrasonic assisted rotary ECDD (UR-ECDD) process for maximizing the material removal rate (MRR), while minimizing the hole overcut (HOC) and circularity error (CE). …”
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MPN-RRT*: A New Method in 3D Urban Path Planning for UAV Integrating Deep Learning and Sampling Optimization by Yue Zheng, Ang Li, Zihan Chen, Yapeng Wang, Xu Yang, Sio-Kei Im

“…The increasing deployment of unmanned aerial vehicles (UAVs) in complex urban environments necessitates efficient and reliable path planning algorithms. While traditional sampling-based methods such as Rapidly exploring Random Tree Star (RRT*) are widely adopted, their computational inefficiency and suboptimal path quality in intricate 3D spaces remain significant challenges. …”
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Enhancing Last-Mile Logistics: AI-Driven Fleet Optimization, Mixed Reality, and Large Language Model Assistants for Warehouse Operations by Saverio Ieva, Ivano Bilenchi, Filippo Gramegna, Agnese Pinto, Floriano Scioscia, Michele Ruta, Giuseppe Loseto

“…Artificial intelligence (AI) techniques are widely used to optimize fleet management, while augmented and mixed reality (AR/MR) technologies are being adopted to enhance warehouse operations. …”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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Actor–Critic Reinforcement Learning for Throughput-Optimized Power Allocation in Energy Harvesting NOMA Relay-Assisted Networks by Faeik T. Al Rabee, Ala'Eddin Masadeh, Sharief Abdel-Razeq, Haythem Bany Salameh

“…During the first phase, the energy-harvesting source communicates with the relay to maximize the data rate while learning an optimal power allocation policy using an actor-critic approach. …”
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A Metaheuristic Approach for a Two-dimensional Fuzzy Version of the Variable Size and Cost Bin Packing Problem by Jorge Herrera Franklin, Alejandro Rosete, Guillermo Sosa-Gómez, Omar Rojas

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Optimal H.264 Scalable Video Scheduling Policies for 3G/4G Wireless Cellular and Video Sensor Networks by Vamseedhar R. Reddyvari, Aditya K. Jagannatham

“…We consider the problem of optimal H.264 scalable video scheduling, with an objective of maximizing the end-user video quality while ensuring fairness in 3G/4G broadband wireless networks and video sensor networks. …”
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High-speed threat detection in 5G SDN with particle swarm optimizer integrated GRU-driven generative adversarial network by R. Shameli, Sujatha Rajkumar

“…The PSO optimizes the network weight of the GAN model to improve the backpropagation while generating the synthetic data (attack data) in the generator model using GRU. …”
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A novel pressure control method for nonlinear shell-and-tube steam condenser system via electric eel foraging optimizer by Serdar Ekinci, Cebrail Turkeri, Davut Izci, Laith Abualigah, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…However, traditional controllers (PI, PD, PID) struggle with nonlinearities and external disturbances, while classical tuning methods (Ziegler-Nichols, and Cohen-Coon) fail to provide optimal parameter selection. …”
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Two-layer multi-objective optimal sizing of electric-hydrogen energy storage with the integration of extreme scenario generation and preference-information decision-making by Zihan Sun, Jian Chen, Yang Chen, Wen Zhang, Tingting Zhang, Yicheng Zhang, Guangsheng Pan

“…Furthermore, an angle preference-based multi-objective particle swarm optimization algorithm is introduced to incorporate the preferences of decision-makers and yield flexible and tailored optimal sizing solutions. …”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…To overcome these challenges, this paper presents ORA-DL (Optimized Resource Allocation using Deep Learning) an advanced framework that integrates deep learning, Internet of Things (IoT)-based sensing, and real-time adaptive control to optimize smart grid energy management. …”
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Parametric Optimization and Assessment of Modern Heritage Shading Screen for a Mid-Rise Building in Arid Climate: Modernizing Traditional Designs by Anwar Ahmad, Lindita Bande, Waleed Ahmed, Kheira Tabet Aoul, Mukesh Jha

“…This research explores how parametric design and optimization based on genetic algorithms (GAs) can improve shading structures to reduce solar radiation and lower cooling energy consumption. …”
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