Optimization underpins many of the challenges that science and technology face on a daily
basis. Recent years have witnessed a major shift from traditional optimization paradigms …

Mathematical optimization is one of the cornerstones of modern engineering research and
practice. Yet, throughout all application domains, mathematical optimization is, for the most …

The preparation of this second edition of our book was triggered by a rush of fresh
developments leading to many interesting results. The text has significantly been enlarged …

This paper considers unconstrained convex optimization problems with time-varying
objective functions. We propose algorithms with a discrete time-sampling scheme to find and …

By incorporating the redefined error monitor function into the network design, an error
redefinition neural network (ERNN) is proposed to control mobile redundant manipulators to …

This article proposes a unifying design framework for dynamic feedback controllers that track
solution trajectories of time-varying generalized equations, such as local minimizers of …

Time-distributed optimization is an implementation strategy that can significantly reduce the
computational burden of model predictive control. When using this strategy, optimization …

Time-varying nonlinear optimization (TVNO) problems are considered as important issues in
various scientific disciplines and industrial applications. In this paper, the continuous-time …

This paper develops online algorithms to track solutions of time-varying constrained
optimization problems. Particularly, resembling workhorse Kalman filtering-based …

We develop algorithms that find and track the optimal solution trajectory of time-varying
convex optimization problems that consist of local and network-related objectives. The …