Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking by Athanasios Sidiropoulos, Dimitrios Bechtsis, Dimitrios Vlachos

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Integrating AI Deep Reinforcement Learning With Evolutionary Algorithms for Advanced Threat Detection in Smart City Energy Management by Fenghua Liu, Xiaoming Li

“…The results from simulated smart city environments demonstrate significant improvements in energy efficiency, cost reduction, and emission control. …”
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Multi-energy System Planning and Configuration Study for Low-Carbon Parks Based on Comprehensive Optimization Objectives by Yang WANG, Fei LU, Ji LI, Zhukui TAN, Zongyu SUN, Wei XU, Zihong SONG, Zhenpeng LIU

“…Secondly, by taking a multi-energy system with triple supply of cooling, heating and power system coupled with ground source heat pump, energy storage, and gas boiler in a typical low-carbon park as an example, a comparative analysis was made on the configuration results and optimization speed with different optimization algorithms, and a study was conducted on the impacts of different optimization objectives such as optimal comprehensive optimization objective and lowest whole life-cycle cost and energy consumption on the capacity optimization configuration results and typical daily operation situation. …”
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A genetic algorithm-based solution for multi-type maximal covering location problem (MMCLP): application to defense and deterrence by J.D. Lessan, Geoff Pond

“…Design/methodology/approach – In our case study, we use open source geographic and demographic data from Canadian sources as inputs to our optimization problem. Due to the complexity of the MIP formulation, we propose a hybrid metaheuristic solution approach, for which a genetic algorithm (GA) is proposed and integrated with local and large neighborhood search operators. …”
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Functional Complete Revascularization as Determined by an Optimized Scoring System After Revascularization: A Post Hoc Analysis from Multi‐Center PANDA III Trial by Rui Zhang, Shaoyu Wu, Qianqian Liu, Changdong Guan, Hao‐Yu Wang, Sheng Yuan, Lihua Xie, Yunfei Huang, Zheng Qiao, Weida Liu, Rui Fu, Lei Feng, Chenggang Zhu, Lei Song, Dong Yin, Kefei Dou

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Optimization of Home Energy Management Systems in Smart Cities Using Bacterial Foraging Algorithm and Deep Reinforcement Learning for Enhanced Renewable Energy Integration by Mohammed Naif Alatawi

“…Significant reductions in total energy consumption and cost, accompanied by improved peak demand management, exemplify the algorithms’ impact. …”
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Microservice Workflow Scheduling with a Resource Configuration Model Under Deadline and Reliability Constraints by Wenzheng Li, Xiaoping Li, Long Chen, Mingjing Wang

“…Experiments on four scientific workflow datasets show that the proposed approach achieves an average cost reduction of 44.59% compared to existing reliability scheduling algorithms, with improvements of 26.63% in the worst case and 73.72% in the best case.…”
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A new stochastic multi-objective model for the optimal management of a PV/wind integrated energy system with demand response, P2G, and energy storage devices by Hossein Faramarzi, Navid Ghaffarzadeh, Farhad Shahnia

“…Optimal energy hub scheduling (EHS) has emerged as a promising strategy for improving the efficiency and flexibility of power systems. …”
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Optimization for Express/Local Train Stop Plans on City Rapid Rail Transit Lines by GUO Jingfan

“…Although the algorithm slightly increases operational costs for enterprises, it significantly reduces passenger travel time costs and improves overall passenger travel accessibility.…”
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Maximizing efficiency and performance of water distribution systems through the implementation of optimization algorithms: A comprehensive analysis of valve and chlorine booster pl... by Mohamadreza Najarzadegan, Mehrtash Eskandaripour

“…By employing advanced optimization algorithms, specifically the Genetic Algorithm (GA) and Slime Mould Algorithm (SMA), the research identifies optimal configurations across two benchmark networks, Jowitt and Xu and GoYang. …”
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Research on the configuration scheme and system parameter optimization of pumps in the component cooling system and sea water system for HPR1000 by Weiguang Zhao, Pei Yu, Xiaobo Zeng, Guangming Fan, Zhaoming Meng, Changqi Yan

“…Based on a mathematical model for CCS and SWS that can be utilized for optimization calculations, we propose and validate an Improved Non-dominated Sorting Genetic Algorithm II (INSGA-II) with good algorithm performance, optimizing for system design costs and total operational costs as objectives, and provide a sensitivity analysis of relevant variables. …”
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Autonomous UAV Path Optimization Using Genetic and Multiobjective Evolutionary Algorithms for Effective Data Retrieval in Cache-Enabled Mobile Ad-Hoc WSNs by Umair B. Chaudhry, Chris Ian Phillips

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Enhanced Reinforcement Learning Algorithm Based-Transmission Parameter Selection for Optimization of Energy Consumption and Packet Delivery Ratio in LoRa Wireless Networks by Batyrbek Zholamanov, Askhat Bolatbek, Ahmet Saymbetov, Madiyar Nurgaliyev, Evan Yershov, Kymbat Kopbay, Sayat Orynbassar, Gulbakhar Dosymbetova, Ainur Kapparova, Nurzhigit Kuttybay, Nursultan Koshkarbay

“…The proposed approach demonstrates the best performance, achieving a 17.2% increase in the packet delivery ratio compared to the traditional Adaptive Data Rate (ADR) algorithm. The proposed DDQN-PER algorithm showed PDR improvement in the range of 6.2–8.11% compared to other existing RL and machine-learning-based works.…”
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Harnessing feature pruning with optimal deep learning based DDoS cyberattack detection on IoT environment by Eunmok Yang, Sooyong Jeong, Changho Seo

“…Besides, the feature pruning process is performed using an improved pelican optimization algorithm (IPOA), which enables the choice of an optimal subset of features. …”
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Application of Twisting Controller and Modified Pufferfish Optimization Algorithm for Power Management in a Solar PV System with Electric-Vehicle and Load-Demand Integration by Arunesh Kumar Singh, Rohit Kumar, D. K. Chaturvedi, Ibraheem, Gulshan Sharma, Pitshou N. Bokoro, Rajesh Kumar

“…The power management controller is a combination of the twisting sliding-mode controller (TSMC) and Modified Pufferfish Optimization Algorithm (MPOA). The proposed method is implemented, and the application results are matched with the Mountain Gazelle Optimizer (MSO) and Beluga Whale Optimization (BWO) Algorithm by evaluating the PV power output, EV power, battery-power and battery-energy utilization, grid power, and grid price to show the merits of the proposed work.…”
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Usability and Perceived Efficiency of an Adaptive Route Optimization Solution for Commercial Vehicles by Florian Anghelache, Nicolae Goga, Constantin Viorel Marian, Dan Alexandru Mitrea, Ionel-Bujorel Pavaloiu

“…At the end of the day, adding these adjustments results in achieving up to a 20% improvement in the accuracy of executed routes, in terms of distance and time, compared to the planned route, outperforming standard optimization algorithms. …”
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Bi-objective green supply chain network design under disruption risk through an extended NSGA-II algorithm by Xiaoqing Wang, Gang Chen, Song Xu

“…The extended algorithm is considered to combine original NSGA-II algorithm with the migration operation of the biogeography-based optimization (BBO) algorithm, thus leading to enrich the diversity of the population and improve the ability of global searching. …”
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Enhancing Harmony Search Metaheuristic Algorithm for Coverage Efficiency, Test Suite Reduction, and Running Time in Combinatorial Interaction Testing by Aminu Aminu Muazu, Ahmad Sobri Hashim

“…Optimization has developed powerful algorithms for solving complex problems efficiently. …”
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Integrated Scheduling Optimization for Multi-Line Production and Transportation of Prefabricated Components Considering Shared Resources by Yiran Dan, Chengshuang Sun, Qianmai Luo

“…With on-time delivery and lower costs as the goals, a scheduling optimization mathematical model is established for this scenario. …”
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Financial Market Evaluation Utilizing an Optimized Deep-Learning Model: A Case Study of the Nikkei 225 by Karthikeyan M P

“…The precision of the stock market forecasts can be improved using metaheuristic algorithms such as the Moth-flame optimizer, which will provide the best optimization of the hyperparameters for an LSTM model. …”
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