Quantum-inspired robust optimization for coordinated scheduling of PV-hydrogen microgrids under multi-dimensional uncertainties by Yunxiao Bai, Yu Sui, Xiaoyu Deng, Xiangbing Wang

“…Stress-testing under scenarios such as 48-hour grid failure, signal-based cyberattacks, and 40% PV output curtailment reveals substantial gains: operational costs are reduced by 9.3%, resilience scores improve by over 20% in adverse conditions, and convergence speed increases by 42% relative to classical optimization. …”
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Comparative techno-economic analysis of grid-connected solar PV-battery and PV-fuel cell systems for educational institutions sustainable academic laboratories by Takele Ferede Agajie, Fuseini Seidu Ibrahim, Isaac Amoussou, Elsabet Ferede Agajie, Eriisa Yiga Paddy, Yayehyirad Ayalew Awoke, Wirnkar Basil Nsanyuy, Mohit Bajaj

“…Techno-economic decision criteria were implemented using MATLAB. Three algorithms were used: Teaching–Learning-Based Optimization (TLBO), Water Cycle Algorithm (WCA), and Improved Grey Wolf Optimization (I-GWO). …”
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Design and energy management research of integrated microgrid with light storage and charging with double-layer optimization scheduling model by Pan Zhai

“…On the basis of considering the uncertainty of photovoltaics, a dual layer optimization scheduling structure with reduced operating costs and equipped with supercapacitors has been proposed. …”
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Research on energy storage planning methods for distributed renewable energy integrated rural power distribution networks by Haoshuai Jia, Renqing Feng, Hai Jiang, Chao Gao, Yue Zhao, Rui Zhang, Ziyi Xuan

“…The optimal locations and capacities of energy storage systems are determined using YALMIP toolbox and the beetle swarm optimization (BSO) algorithm, and the proposed method is validated on a modified IEEE 33-bus system. …”
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Algorithm for assigning different 6-month short-term chemotherapy regimens in patients with drug-resistant tuberculosis: how to make the right choice for the clinician by Yu.I. Feshchenko, N.A. Lytvynenko, L.M. Protsyk, M.V. Pohrebna, Yu.O. Senko

“…For patients with pre-XDR-TB, the BPaL regimen offers the best balance of efficacy, tolerability, and cost-effectiveness. The proposed prescription algorithms enable a personalized treatment approach and improve therapeutic outcomes.…”
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Collaborative Optimization of Passenger Control Strategy and Train Operation Plan with Variable Formations for a Rail Transit Network by Yonghao Yin, Jun Chen, Wenrui Zhao

“…We proposed a passenger control strategy and train operation plan collaborative optimization (PCS&TOP) model to schedule the train operation that improves the efficiency of passengers’ travel and reduces the cost of train operation for a rail transit network. …”
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Artificial Intelligence-Driven Approach to Optimizing Boiler Power Generation Efficiency: The Advanced Boiler Combustion Control Model by Kyu-Jeong Lee, So-Won Choi, Eul-Bum Lee

“…Consequently, achieving stable combustion control of these gases is critical for improving boiler efficiency. This study developed the advanced boiler combustion control model (ABCCM) by combining the random forest (RF) and classification and regression tree (CART) algorithms to optimize the combustion of steam power boilers using steel by-product gases. …”
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Tackling the Optimal Phasor Measurement Unit Placement and Attack Detection Problems in Smart Grids by Incorporating Machine Learning by Ramzi Al-Sharawi, Abdelfatah Ali, Mostafa Shaaban, Nasser Qaddoumi, Mohamed S. Abdalzaher

“…Existing research primarily addresses cybersecurity by focusing on the optimal placement of phasor measurement units (PMUs) to ensure topological observability and minimize system costs, followed by developing AI-based attack detection algorithms. …”
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Optimization of Laser-Induced Hybrid Hardening Process Based on Response Surface Methodology and WOA-BP Neural Network by Qunli Zhang, Jianan Ling, Zhijun Chen, Guolong Wu, Zexin Yu, Yangfan Wang, Jun Zhou, Jianhua Yao

“…This study uses Box–Behnken design (BBD) experiments to analyze key process parameters and develops response surface methodology (RSM) and whale-optimization-algorithm-optimized back-propagation neural network (WOA-BPNN) models for prediction and optimization. …”
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Optimal energy management for multi-energy microgrids using hybrid solutions to address renewable energy source uncertainty by M. Siva Ramkumar, Jaganathan Subramani, M. Sivaramkrishnan, Arunkumar Munimathan, Goh Kah Ong Michael, Mohammad Mukhtar Alam

“…In this study, a new hybrid algorithm is used for system modelling and low-cost, optimal management of Micro Grid (MG) networked systems. …”
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Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

“…Results demonstrate significant improvements in system reliability, cost efficiency, and flexible operation, validating the effectiveness of ANN-based AL to optimize EHs management and ensure sustainable operation complexities. …”
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Synergistic Effects of Energy Storage Systems and Demand-Side Management in Optimizing Zero-Carbon Smart Grid Systems by Zeyad A. Almutairi, Ali M. Eltamaly

“…An advanced load and weather-forecasting strategy is introduced for improving grid planning and management. An advanced optimization algorithm enhances grid stability and efficiency. …”
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Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints by Daxing Lei, Yaoping Zhang, Zhigang Lu, Hang Lin, Yifan Chen

“…To address these challenges, this study proposes a hybrid ML model that integrates a multilayer perceptron (MLP) with the slime mold algorithm (SMA), termed the SMA-MLP model. While MLP exhibits strong nonlinear mapping capability, SMA enhances its training process through global optimization and parameter tuning, thereby improving predictive accuracy and robustness. …”
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Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

“…This paper uses a particle swarm optimisation (PSO) algorithm to determine the optimal values for the injected components. …”
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Prediction of UHPC mechanical properties using optimized hybrid machine learning model with robust sensitivity and uncertainty analysis by ZhiGuang Zhou, Jagaran Chakma, Md Ahatasamul Hoque, Vaskar Chakma, Asif Ahmed

“…Each dataset was standardized and split into training (80%) and testing (20%) subsets. Hyperparameter optimization was conducted using a random search algorithm to improve prediction accuracy. …”
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Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…By using Stochastic Forest, an improvement in decision accuracy can be attained to the extent of 15–20%, together with a cut in costs of about 10%. …”
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Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…This study focuses on the multi-objective coordination problem in university campus planning and design, proposing an optimized methodology integrating an improved multi-objective decision-making framework. …”
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Distributionally robust optimal scheduling of flexible distribution networks considering dynamic spatio-temporal correlation of renewable energy by Shunxiang Yu, Xiaoming Dong, Chengfu Wang, Tianguang Lu

“…By utilizing the 1-norm and ∞-norm to characterize the uncertainty sets between sources and loads, this strategy effectively minimizes operational costs while ensuring robust performance. The proposed model is linearized and relaxed through second-order cone programming and solved using the column and constraint generation (C&CG) algorithm. …”
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Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This complex multi-million-dollar problem involves optimizing multiple parameters using computationally intensive reservoir simulations, often employing advanced algorithms such as optimization algorithms and machine/deep learning techniques to find near-optimal solutions efficiently while accounting for uncertainties and risks. …”
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On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR by Yuting Zhu, Giuseppe Grieco, Jiarong Lin, Marcos Portabella, Xiaoqing Wang

“…The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. …”
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