Abstract: This letter focuses on a safety-critical solution to equality-constrained nonlinear programming, where the cost and the constraints vary continuously over time. To address this problem, we ...

Factor graph optimization serves as a fundamental framework for robotic perception, enabling applications such as pose estimation, simultaneous localization and mapping (SLAM), structure-from-motion ...

Researchers have developed a novel multi-constraint optimization method that significantly improves the efficiency of reinforcement learning in complex environments. This new algorithm, called ...

We study some nonlinear optimal control problems under state constraint. We construct extremal flows by differential-algebraic equations to solve an optimal control problem subject to mixed ...

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In today’s fast-paced, ever-evolving world, the complexity of challenges faced in both business and everyday life requires a shift in how we approach problem solving. Traditional linear thinking, ...

Bayesian statistics remain popular for addressing inverse problems, whereby quantities of interest are determined from their noisy and indirect observations. Bayes’ theorem forms the foundation of ...

School of Mathematics, Liaoning Normal University, Dalian, China. In recent years, research in this field has continued to deepen, involving multiple different directions. As an example, a research ...

In the realm of competitive programming, both human participants and artificial intelligence systems encounter a set of unique challenges. Many existing code generation models struggle to consistently ...

Linear solvers are major computational bottlenecks in a wide range of decision support and optimization computations. The challenges become even more pronounced on heterogeneous hardware, where ...