Two-Dimensional Beam Selection by Multiarmed Bandit Algorithm Based on a Quantum Walk by Maki Arai, Tomoki Yamagami, Takatomo Mihana, Ryoichi Horisaki, Mikio Hasegawa

“…This article proposes a novel beam selection method using a multiarmed bandit (MAB) algorithm based on a quantum walk (QW) principle, aimed at improving system performance. …”
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DLE-YOLO: An efficient object detection algorithm with dual-branch lightweight excitation network by Peitao Cheng, Xuanjiao Lei, Haoran Chen, Xiumei Wang

“…Thirdly, the localization loss utilizes SIoU loss to further optimize the accuracy of the bounding box. Our method achieves a mAP value of 46.0% on the MS-COCO dataset, which is a 2% mAP improvement compared to the baseline YOLOv5-m, while bringing a 19.3% reduction in parameter count and a 12.9% decrease in GFLOPs. …”
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A Cooperative Generation Expansion Planning of Microgrids to Improve the Resiliency of Active Distribution Networks by Mohammad Hossein Atazadegan, Esmaeel Rokrok, Meysam Doostizadeh

“…In this case, the multi objective optimization problem, including the objective functions of total cost and environmental pollution, has been solved using fuzzy decision-making and multi-objective improved golden ratio optimization algorithm based on the Pareto front.…”
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A Cellular Automata-Based Crossover Operator for Binary Chromosome Population Genetic Algorithms by Doru Constantin, Costel Bălcău

“…After presenting the fundamental elements regarding cellular automata with specific examples for one- and two- dimensional cases, the the most widely used crossover operators in applications with genetic algorithms are described, and the crossover operator based on cellular automata is defined. …”
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Classification and spectrum optimization method of grease based on infrared spectrum by Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li

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Optimizing demand charge of data center base on PE method by Yan HUANG, Peng WANG, Gao-hui XIE

“…Demand charge and energy charge are the two main components of data center electricity cost,previous re-searches have not take demand charge into consideration.PEDC algorithm was proposed by modeling time slot,work-load,service quality constraint and response time constraint.With PEDC algorithm peak power was decreased by partial execution on the condition of service quality constrai and response time constraint.PE method was executed in the heavy loaded time slots to reduce peak power so as to ize demand charge.Energy charge and total charge were also optimized.By comparing with four algorithms and with accurately predicted,PEDC algorithm can reduce elec-tricity cost by 5.9%~12.7% and improve cluster utilization 1.32 times.…”
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Operation Optimization of Multiphase Pollutant Treatment Considering Carbon Emissions by Guo Yu, Dongjie Zhang, Hailong Deng, Chao Jiang, Quanling Zhang

“…Aiming to improve the treatment of multiphase pollutants, this study builds a three-objective optimization model by considering the optimization of treatment effect, energy consumption, and an innovatively constructed optimization objective of direct and indirect carbon emissions. …”
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A State-of-the-Art Survey on Advanced Electromagnetic Design: A Machine-Learning Perspective by Masoud Salmani Arani, Reza Shahidi, Lihong Zhang

“…This paper presents an overview of recent developments in optimization and design automation techniques for EM-component design and modeling. …”
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Network slicing resource allocation strategy based on joint optimization by Zaijian WANG, Huimin GU

“…To improve network resource utilization that was decreased by different applications with different requirements in 5G networks, a network slicing resource allocation strategy based on joint optimization was proposed, which was utilized to maximize both network resource utilization and network revenue by comprehensively considering in tra-slice and inter-slice resource schedule.Firstly, the user’s average satisfaction function was defined in the inter-slicing resource allocation problem.Furthermore, in terms of the number of users, slicing schedule delay and priority, a proportional fair resource allocation algorithm based on quality of service (QoS) was proposed, which was employed to achieve the best tradeoff between fairness and the users’ requirements among slices.Secondly, after two functions (service degradation and resource migration) were introduced in the inter-slice resource schedule problem, two price models were established for internal access users and external access users respectively, where congestion and non-congestion conditions were analyzed.According to the proposed price models, a Stackelberg game between the base station and users was constructed, and a global search algorithm with low complexity was leveraged to obtain the best response of the game, where the best tradeoff between the base station revenue and user utility was obtained.Simulation results show that the proposed strategy can effectively improve resource utilization and network revenue while reducing network congestion.Therefore, it can better realize fairness in resource allocation.…”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…This research utilizes swarm intelligence algorithms—Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
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Cooperative trajectory optimization for multiple connected vehicles at an unsignalized intersection by Hao Yang, Xianyang Li, Duoyang Qiu, Xiaomeng Zhu

“…Through numerical simulation analysis of intersection scenarios including crossroad and roundabout, the results demonstrate that the proposed algorithm can achieve optimal trajectories for multi-vehicle cooperative motion while ensuring safe vehicle operation, which improves the efficiency of future intelligent traffic networks.…”
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Enhancing mass vaccination programs with queueing theory and spatial optimization by Sherrie Xie, Maria Rieders, Srisa Changolkar, Bhaswar B. Bhattacharya, Elvis W. Diaz, Michael Z. Levy, Michael Z. Levy, Ricardo Castillo-Neyra, Ricardo Castillo-Neyra

“…Queueing theory offers a framework for modeling queue formation at vaccination sites and its effect on vaccine uptake.MethodsWe developed an algorithm that integrates queueing theory within a spatial optimization framework to optimize the placement of mass vaccination sites. …”
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A Multi-Objective Bio-Inspired Optimization for Voice Disorders Detection: A Comparative Study by Maria Habib, Victor Vicente-Palacios, Pablo García-Sánchez

“…The optimization problem has been formulated as a wrapper-based algorithm for feature selection and multi-objective optimization relying on four machine learning algorithms: K-Nearest Neighbour algorithm (KNN), Random Forest (RF), Multilayer Perceptron (MLP), and Support Vector Machine (SVM). …”
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Lightweight highland barley detection based on improved YOLOv5 by Minghui Cai, Hui Deng, Jianwei Cai, Weipeng Guo, Zhipeng Hu, Dongzheng Yu, Houxi Zhang

“…The results show that the improved YOLOv5 model has a significant improvement in detection performance. …”
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Optimization of emergency logistics for urban flooding with consideration of rainfall effects by Peiwen Zhang, Chenxing Zhang, Pan Zhang, Xuxian Yan, Huawei Yang

“…This study proposes a two-stage optimization framework for emergency logistics. First, a supply distribution model is developed by integrating resource scarcity indices and disaster severity indices, optimized through a simulated annealing algorithm. …”
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OPTIMIZATION OF STOCK KEEPING AND SPACE UTILIZATION POLICY FOR A WAREHOUSE by Basel Zbeda, Mazen Sımı, Husam Jehad Hasan Omar, Mhd Hazem Alhammamı, Faris Albakar, Zehra Düzgit

“…The warehouse dataset includes items of various sizes, and the goal is to allocate these items into bins most efficiently. Experimental results demonstrate that the FFD and BFD algorithms outperform the NFD algorithm. …”
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Object Detection Method of Inland Vessel Based on Improved YOLO by Yaoqi Wang, Jiasheng Song, Yichun Wang, Rongjie Wang, Hongyu Chen

“…Finally, GSConv and VovGSCSP in Slim-Neck are introduced into the Neck network to optimize the network architecture, reduce part of the model complexity, and further improve the performance of the model. …”
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Novel Design and Optimization of Porous Titanium Structure for Mandibular Reconstruction by Renshun Liu, Yuxiong Su, Weifa Yang, Xiaobing Dang, Chunyu Zhang, Ruxu Du, Yong Zhong

“…The design and optimization technique of the porous structure presented in this paper can be used to control peak stress, improve porosity, and fabricate a lightweight scaffold, which provides a potential solution for mandibular reconstruction.…”
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Dynamic optimization of intersatellite link assignment based on reinforcement learning by Weiwu Ren, Jialin Zhu, Hui Qi, Ligang Cong, Xiaoqiang Di

“…Different from the swarm intelligence method in principle, this algorithm models the combinatorial optimization problem of links as the optimal sequence decision problem of a series of link selection actions. …”
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Robot Task-Constrained Optimization and Adaptation with Probabilistic Movement Primitives by Guanwen Ding, Xizhe Zang, Xuehe Zhang, Changle Li, Yanhe Zhu, Jie Zhao

“…We separate ProMPs as Gaussians at each timestep and minimize Kullback–Leibler (KL) divergence, with a gradient ascent–descent algorithm performed to obtain optimized ProMPs. Given optimized ProMPs, we outline a unified robot movement adaptation method for extending from a single obstacle to multiple obstacles. …”
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