An overview of AC and DC microgrid energy management systems by Mohamed G Moh Almihat

“…Management of microgrid energy employs stochastic and robust optimization. Control and predictive modeling (MPC) generates energy management plans for microgrids. …”
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Hybrid Ship Unit Commitment with Demand Prediction and Model Predictive Control by Janne Huotari, Antti Ritari, Jari Vepsäläinen, Kari Tammi

“…This opens up the possibility for using stochastic or robust optimization methods for unit commitment optimization in future studies.…”
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Data-driven two-stage sparse distributionally robust risk optimization model for location allocation problems under uncertain environment by Zhimin Liu

“…Robust optimization is a new modeling method to study uncertain optimization problems, which is to find a solution with good performance for all implementations of uncertain input. …”
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A sustainable scheduling system for medical equipment: Towards net zero goals for green healthcare by Baotong Wu, Qi Tang

“…Then, this paper constructs and solves a multi-objective robust optimization model by collecting the patient's travel information and the medical pressure information of each region. …”
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Secure Authentication and Data Transmission for Patients Healthcare Data in Internet of Medical Things by Anup Patnaik, Krishna K. Prasad

“…A hybrid optimization approach, combining robust optimization and genetic algorithms, is employed to select unique and distinct keys. …”
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Multi-Objective Optimal Sizing of HRES under Multiple Scenarios with Undetermined Probability by Kaiwen Li, Yuanming Song, Rui Wang

“…Furthermore, when applying the robust optimization method, it is difficult to fully use existing data to describe uncertain parameters in the form of intervals. …”
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Optimal Scheduling of Integrated Energy System Considering Integration of Electric Vehicles and Load Aggregators by WANG Jing, XING Haijun, WANG Huaxin, PENG Sijia

“…First, the response rate model and EV uncertainty model based on economic incentive are constructed. Then, the robust optimization model of EV is built, and the load demand of EV travel uncertainty is analyzed. …”
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Optimized Design of Rotor Barriers in PM-Assisted Synchronous Reluctance Machines With Taguchi Method by Maryam Naseh, Saeed Hasanzadeh, Seyed Mohammad Dehghan, Hossein Rezaei, Ameena Saad Al-Sumaiti

“…The poor power factor (PF) and high torque ripple are the main challenges of SynRMs, which necessitate robust optimization improving the mentioned demerits. However, the optimization algorithms usually rely on complex analytical models; in this paper, in order to optimize, the design of experiments with the Taguchi method has been used. …”
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Chance-Constrained Based Voltage Control Framework to Deal with Model Uncertainties in MV Distribution Systems by Bashir Bakhshideh Zad, Jean-François Toubeau, François Vallée

“…The performance of proposed CC voltage control methods is finally tested in comparison with that of the robust optimization. Simulation results confirm the accuracy of confidence level expected from the proposed CC voltage control formulations. …”
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Distributionally robust learning-to-rank under the Wasserstein metric. by Shahabeddin Sotudian, Ruidi Chen, Ioannis Ch Paschalidis

“…It has been shown that Distributionally Robust Optimization (DRO) is resilient against various types of noise and perturbations. …”
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Distributionally robust learning-to-rank under the Wasserstein metric by Shahabeddin Sotudian, Ruidi Chen, Ioannis Ch. Paschalidis

“…It has been shown that Distributionally Robust Optimization (DRO) is resilient against various types of noise and perturbations. …”
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Gradient Subgroup Scanning for Distributionally and Outlier Robust Models by Jung, Luann

“…Previous approaches for reducing the discrepancy between average and worst-group accuracies typically require expensive known subgroup annotations for either every training data point (as is the case in group distributionally robust optimization (DRO)), or every validation data point. …”
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Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites by Garcia Burgos, Axel

“…Techniques in robust optimization and formal verification methods are used (1) to examine the stability and robust performance of a satellite controller that considers six-dimensional, uncertain state, and often unmodeled dynamics during rendezvous and proximity operations, and (2) to explore the synthesis of control Lyapunov/barrier functions (CLFs/CBFs) using neural networks and stochastic gradient descent to provide safety-aware filtering for the fuel-optimal control policies. …”
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Yield-driven iterative robust circuit optimization algorithm by Li, Yan, Stojanovic, Vladimir Marko

“…This paper proposes an equation-based multi-scenario iterative robust optimization methodology for analog/mixed-signal circuits. …”
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Machine Learning with Operational Costs by Tulabandhula, Theja, Rudin, Cynthia

“…We also show that learning with operational costs is related to robust optimization.…”
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Interactions between learning and decision making by Tulabandhula, Theja

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Design of robust Var reserve contract for enhancing reactive power ancillary service market efficiency by Zou, Yunyang, Xu, Yan

“…Settlement of day-ahead Var reserve contract is formulated as a two-stage robust optimization (TSRO) model considering worst case of uncertainty realization and potential market power that may arise in hourly-ahead market. …”
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Medium access control for dynamic spectrum access in cognitive radio networks : analysis under uncertainty by Dong, Qiumin, Niyato, Dusit, Wang, Ping

“…In this case, a robust optimization method to study the Markov chain with uncertainty is applied to obtain the stationary probabilities of the queueing model under uncertainty. …”
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Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems by Hyreil A., Kasdirin, N. M., Yahya, M. S. M., Aras, Tokhi, M. O.

“…Therefore, the idea of hybridization between IWO and FA is to achieve a more robust optimization technique, especially to compensate for the deficiencies of the individual algorithms. …”
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Research on joint optimization model and algorithm of multi‐area generation and reserve with considering its availability by Dan Xu, Fang Liang, Qian Cheng, Jingyang Zhou, Junjie Tang

“…The joint generation and reserve optimization sub‐model, together with the reserve check sub‐model, constitutes the two‐stage robust optimization model in this paper. The column‐and‐constraint generation (C&CG), algorithm is adopted to solve the proposed model. …”
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