Expected Length of the Shortest Path of the Traveling Salesman Problem in 3D Space by Hongtai Yang, Xiaoqian Lu, Xinan Zhou, Rong Zheng, Yugang Liu, Siyu Tao

“…Under each scenario, the specified number of demand points is randomly generated, and an improved genetic algorithm and Gurobi are used to find the shortest path. …”
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Green and Reliable Freight Routing Problem in the Road-Rail Intermodal Transportation Network with Uncertain Parameters: A Fuzzy Goal Programming Approach by Yan Sun

“…In this study, the author focuses on modeling and optimizing a freight routing problem in a road-rail intermodal transportation network that combines the hub-and-spoke and point-to-point structures. …”
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Deep Reinforcement Learning-Based Attention Decision Network for Agile Earth Observation Satellite Scheduling by Dongning Liu, Guanghui Zhou

“…Moreover, a start-time-shift-based local search is proposed to improve the observation plan generated by the ADN model. …”
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Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends by Chen Boshan

“…Second, the research focuses on key AI applications in quantitative investment, including multi-factor model optimization, high-frequency market risk management, multimodal data integration, and algorithmic trading enhancement. …”
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Boundary Guidance Strategy and Method for Urban Traffic Congestion Region Management in Internet of Vehicles Environment by Chuanxiang Ren, Zhen Wang, Changchang Yin, Hui Xu, Li Wang, Luyao Guo, Juntao Li

“…Meanwhile, a method for the boundary guidance strategy is presented in which the macroscopic fundamental diagram (MFD) is used to determine the optimal accumulation, a traffic flow equilibrium model is established to calculate the real-time accumulation, and a fuzzy adaptive PID control algorithm is designed to calculate the optimal traffic inflow of the traffic congestion region. …”
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Robust fuzzy dynamic integrated environmental-economic-social scheduling considering demand response and user’s satisfaction with electricity under multiple uncertainties by Hong Zhang, Qianwei Xi, Lei Chen, Yong Min, Xiongxiong Fan, Wenjin Fang, Nan Tian, Fei Xu

“…Taking the lowest comprehensive operation cost as the economic objective, the smallest emissions of CO2 and atmospheric pollutants as environmental objective and the largest user’s comprehensive satisfaction with electricity as the social objective, based on the robust fuzzy theory, the multi-objective uncertainty optimal scheduling model is constructed, which is transformed into deterministic model and then solved by intelligent optimization algorithm. …”
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From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…Utilizing a combination of statistical pre-processing, intelligent generative models, visual data transformations and deep learning, the methodology offers a comprehensive approach to enhancing production efficiency, ensuring superior process control and improving the quality of HPDC products. …”
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Editorial by Christian Gütl

“…Besma Hezili and Hichem Talbi from Algeria address the collaborative auto-diversified optimization scheme (CADOS) for solving continuous and combinatorial optimization problems by exploring the synergy of various optimization algorithms and enhance their effectiveness and efficiency, particularly for higher-dimensional problems. …”
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TDMA-based user scheduling policies for federated learning by Meixia TAO, Dong WANG, Rui SUN, Naifu ZHANG

“…To improve the communication efficiency in FL (federated learning), for the scenario with heterogeneous edge user's computing capacity and channel state, a class of time division multiple access (TDMA) based user scheduling policies were proposed for FL.The proposed policies aim to minimize the system delay in each round of model training subject to a given sample size constraint required for computing in each round.In addition, the convergence rate of the proposed scheduling algorithms was analyzed from a theoretical perspective to study the tradeoff between the convergence performance and the total system delay.The selection of the optimal batch size was further analyzed.Simulation results show that the convergence rate of the proposed algorithm is at least 30% higher than all the considered benchmarks.…”
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Research on Fuzzy Decision-Making Method of Task Allocation for Ship Multiagent Collaborative Design by Jinghua Li, Yiying Wang, Boxin Yang, Qinghua Zhou, Feihui Yuan

“…Finally, through example verification and comparative analysis with the Round-Robin algorithm (RR) and the Weighted Round-Robin (WRR) algorithm, the validity, feasibility, and stability of the multidesign agent-task allocation decision-making method proposed in this paper are verified, and it is proved that the task allocation method takes the bilateral needs of the task and the design agent into account, solves the optimal allocation strategy of collaborative design tasks, and realizes the balanced allocation between the ship collaborative design task and the design agent.…”
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Research on detection and tracking methods of unmanned ship water targets based on light vision by LIU Yibo, QIU Xinyu, WANG Tianhao, GAOYAN Xiusong, WANG Yintao

“…In terms of target detection, the YOLOv7 algorithm is used, which effectively improves the accuracy and recall rate of target detection by optimizing the loss function. …”
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Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain by Henning Strubelt, Sebastian Trojahn, Sebastian Lang, Abdulrahman Nahhas

“…This paper deals with the optimization of logistics processes at an underground waste storage site by means of solving scheduling issues and reducing setup times, with the help of a simulation model. …”
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Integrating Social Determinants of Health in Machine Learning–Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study by Seung-Yup Lee, Leslie W Hayes, Bunyamin Ozaydin, Steven Howard, Alison M Garretson, Heather M Bradley, Andrew M Land, Erin W DeLaney, Amy O Pritchett, Amanda L Furr, Ashleigh Allgood, Matthew C Wyatt, Allyson G Hall, Jane C Banaszak-Holl

“… BackgroundThe use of both clinical factors and social determinants of health (SDoH) in referral decision-making for case management may improve optimal use of resources and reduce outcome disparities among patients with diabetes. …”
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Automatic text generation system for endangered languages based on conditional generative adversarial networks by Zhong Luo

“…Future research directions include optimizing CGAN parameters using algorithms like particle swarm optimization, refining discriminator outputs in loss calculations, and incorporating cultural and linguistic features specific to endangered languages to improve the quality of the generated texts.…”
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AI-driven energy management system based on hesitant bipolar complex fuzzy Hamacher power aggregation operators and their applications in MADM by Walid Emam, Hafiz Muhammad Waqas, Tahir Mahmood, Ubaid ur Rehman, Dragan Pamucar

“…Abstract Artificial Intelligence (AI) based energy management systems utilize sophisticated AI algorithms to improve and control the consumption of energy in various sectors, such as power utilities, industrial systems, and smart buildings. …”
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Integrated Additive Manufacturing Trajectory Control and Repair Management for Spiral Bevel Gear Using Fractional-Order PID and Adaptive Fuzzy Neural Inference System by Hiyam Adil Habeeb, Abdul Hadi Azman, Mohd Rizal Alkahari, Dzuraidah Abd Wahab, Nurhasyimah Abd Aziz

“…Design optimization of mechanical system components, such as spiral bevel gears, is important due to their complex geometry and design constraints. …”
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Modernizing the Design Process for US Organ Allocation Policy: Toward a Continuous Distribution Policy for Kidneys by Elijah Pivo, PhD(c), James Alcorn, JD, Dimitris Bertsimas, PhD, Sarah E. Booker, MPH, Keighly Bradbrook, PhD, Thomas G. Dolan, MS, Lindsay V. Larkin, BA, Kayla R. Temple, BA, Nikolaos Trichakis, PhD

“…This improvement enabled the simulation of thousands of allocation policies, allowing the introduction of multiobjective optimization as a primary method for policy design. …”
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Designing a Sustainable Supply Chain Network for Perishable Products Integrating Internet of Things and Mixed Fleets by Lihong Pan, Xialian Li, Miyuan Shan

“…The second objective aims to maximize service levels, which are measured by product quality and on-time delivery. The model is solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). …”
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Adaptive distributed stochastic deep reinforcement learning control for voltage and frequency restoration in islanded AC microgrids with communication noise and delay by Nima Mahdian Dehkordi, Vahab Nekoukar

“…Distinct from prior DRL applications, our method rigorously couples Lyapunov-based stability guarantees with DRL-based gain tuning, ensuring formal stability despite stochastic disturbances and model uncertainties. This hybrid framework facilitates real-time optimization of control policies, contributing to improved resilience and robustness under realistic network conditions. …”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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