Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode by DENG Chengyuan, LU Jinsheng, ZHU Changfeng, SUN Yuanguang, MA Bin

“…The MTSP ( multiple traveling salesman problem) is introduced to construct an optimized train stock utilization model during the transition period from peak to off-peak passenger flow in urban rail transit. …”
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…Furthermore, maintenance tasks are adaptively scheduled using built-in reinforcement learning (RL) and optimized model parameters are fine-tuned for improved predictive accuracy using Bayesian optimization. …”
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Collaborative Optimization of Container Liner Slot Allocation and Empty Container Repositioning Within Port Clusters by Wenmin Wang, Cuijie Diao, Wenqing He, Zhihong Jin, Zaili Yang

“…Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. …”
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An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning by L. Ravi Kumar, Ravi Kumar Tata, T. R. Mahesh, Endris Mohammed Ali

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Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue by Chongde CHEN, Qiang GUO, Ziqiu SONG, Yang HU

“…In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. …”
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Optimization design of combustion chamber for a non-road diesel engine in high-altitude region by Yibing Hou, Jun Wang, Jilin Lei, Liang Chen

“…Subsequently, a Latin hypercube sampling (LHS) approach was employed for experimental design, and a back-propagation (BP) neural network was utilized to develop a surrogate model. Finally, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to perform multi-objective optimization, and the technique for order preference by similarity to ideal solution (TOPSIS) was utilized to select the optimal combustion chamber structural parameters suitable for high-altitude regions. …”
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Electromagnetic Analysis and Multi-Objective Design Optimization of a WFSM with Hybrid GOES-NOES Core by Kyeong-Tae Yu, Hwi-Rang Ban, Seong-Won Kim, Jun-Beom Park, Jang-Young Choi, Kyung-Hun Shin

“…The optimized WFSM achieved a 13.97% increase in power density and a 1.0% improvement in efficiency compared to the baseline NOES model. …”
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Optimizing multimodal timetable synchronization of intercity railway and metro for the first service period during holidays by Yan Liu, Quan Zhang, Xuan Li, Yang Shi

“…To solve the model, an improved artificial bee colony algorithm (ABC) is designed, incorporating adaptive neighbour search and simulated annealing techniques. …”
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An intelligent stochastic optimization approach for air cargo order allocation under carbon emission constraints. by Zhenzhong Zhang, Ling Zhang, Deqiang Fu, Weichun Li

“…The method finds the optimal solution through an improved adaptive large-scale neighborhood search algorithm and uses a scenario generation technique to generate the scenarios required for evaluating candidate solutions to the high-dimensional stochastic optimization problem. …”
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Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…The proposed model trained with all weeks’ data demonstrated superior performance, showing significant improvements in F1-scores and recall, particularly for the minority class of at-risk students. …”
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UAV-based multitier feature selection improves nitrogen content estimation in arid-region cotton by Fengxiu Li, Fengxiu Li, Chongqi Zhao, Chongqi Zhao, Yingjie Ma, Yingjie Ma, Ning Lv, Yanzhao Guo, Yanzhao Guo

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Optimizing Scheduled Virtual Machine Requests Placement in Cloud Environments: A Tabu Search Approach by Mohamed Koubàa, Abdullah S. Karar, Faouzi Bahloul

“…Our algorithm demonstrates significant improvements over existing placement methods, achieving up to a 15% increase in resource efficiency compared to baseline approaches. …”
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Energy-efficient optimization strategy based on elastic data migration in big data streaming platform by Yonglin PU, Xiaolong XU, Jiong YU, Ziyang LI, Binglei GUO

“…Focused on the problem that the stream computing platform was suffering from the high energy consumption and low efficiency due to the lack of consideration for energy efficiency in designing process, an energy-efficient optimization strategy based on elastic data migration in big data streaming platform (EEDM-BDSP) was proposed.Firstly, models of the load prediction and the resource judgment were set up, and the load prediction algorithm was designed, which predicted the load tendency and determine node resource occupancy, so as to find nodes of resource overload and redundancy.Secondly, models of the resource constraint and the optimal data migration were set up, and the optimal data migration algorithm was proposed, which data migration for the purpose of improving node resource utilization.Finally, model of the energy consumption was set up to calculate the energy consumption saved by the cluster after data migration.The experimental results show that the EEDM-BDSP changes node resources in the cluster can responded on time, the resource utilization and the energy-efficient are improved.…”
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Numerical simulation of optimal jet angle of water jet assisted disc cutter rock breaking by Anxin WANG, Yiqiang LU, Sheng ZHANG, Jianhong MA, Zhanbiao YANG, Hongyun FAN

“…Aiming at the reasonable determination of the optimal rock breaking impact angle of water jet assisted hob, a discrete element model of equivalent crystalline rock material based on Thiessen polygon algorithm was built. …”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid, Hamza Kheddar, Noureddine Batel, Muhammad E. H. Chowdhury

“…The optimal model configuration, using TCN-MHA-Bi-GRU with a kernel size of 16, achieved a compact model size of 788K parameters and recorded training, and validation losses of 0.0350 and 0.0446, respectively. …”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…A multi-objective optimization model is also established, further illustrating the algorithm’s performance and its effectiveness in balancing the number of sensors and coverage rate. …”
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Multi-Objective Optimization Method for High-Efficiency and Low-Consumption Wire Rope Greasing Process by Fan Zhou, Yuemin Wang, Ruqing Gong, Binghui Tang

“…Weight coefficients are introduced to transform the multi-objective optimization model into a single-objective optimization model, which is then solved using an improved genetic algorithm. …”
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Wear analysis and optimization of nanoclay and copper coated carbon fiber strengthened hybrid aluminium composite by N. Senthilkumar, K. Gajalakshmi, K. Palanikumar, B. Deepanraj, Abdul Rahman Afzal

“…The adopted metaheuristic nature-inspired evaporation rate-based water cycle algorithm yields identical results and quickly converges to optimal conditions, resulting in a combined objective function of 157.67.…”
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DBO-DELM Method for Predicting Rolling Forces in Cold Rolling by LI Xiaoyang, PIAO Chunhui, WANG Xuelei, ZHANG Mingzhi

“…Aiming at the problems of many assumptions, large computational errors and poor generalisation performance of the traditional rolling force prediction model, a cold rolling force prediction model (DBO-DELM) using the dung beetle optimizer algorithm (DBO) to optimise the deep extreme learning machine (DELM) is proposed. …”
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Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty by Junjie Qiao, Xiaofang Meng, Weigang Zheng, Pengxue Huang, Tiefeng Xu, Yupeng Xu

“…The constraints, including node voltage and energy storage device, are considered, and the model is solved using the improved grey wolf optimization algorithm. …”
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