(Extended Abstract) Stochastic programming is an optimization technique that incorporates random variables as parameters. Because it better reflects the uncertain real world than its traditional deterministic counterpart, stochastic programming has drawn increasingly more attention among decision-makers, and its applications span many fields including financial engineering , health care, commun...

Neural network controllers have become popular in control tasks thanks to their flexibility and expressivity. Stability is a crucial property for safety-critical dynamical systems, while stabilization of partially observed many cases, requires retain process long-term memories the past. We consider important class recurrent neural networks (RNN) as dynamic nonlinear uncertain partially-observed...

Rapid and accurate rendezvous proximity operations for spacecraft are crucial to the success of most space missions. In this paper, a sequential convex programming method, combined with first-order second-order Birkhoff pseudospectral methods, is proposed autonomous spacecraft. The original nonlinear nonconvex close-range problem thrust constraints no-fly zone converted into its version by usin...

Starting from the theory of elastic plates, we derive a non-linear one-dimensional model for ribbons with thickness t, width and length ℓ, assuming t≪a≪ℓ. It takes form rod specific constitutive law accounting both stretching bending ribbon mid-surface. The is asymptotically correct can handle finite rotations. Two popular theories be recovered as limiting cases, namely Kirchhoff’s small twisti...

For each countable ordinal α, let Sα be the Schreier set of order α and XSα corresponding space α. In this paper, we prove several new properties these spaces. 1. If is nonzero, then XSαpossesses λ-property Aron Lohman a (V)-polyhedral in sense Fonf Vesely. 2. nonzero 1<p<∞, p-convexification p possesses uniform Lohman. 3. ∗ has λ-property. 4. n∈N, if T:XSn→XSnis an onto linear isometry, Tei=±e...

The lift-and-project technique is a systematic way to generate valid inequalities for a mixed binary program. The technique is interesting both on the theoretical and on the practical point of view. On the theoretical side it allows you to construct the inequality description of the convex hull of all mixed-{0, 1} solutions of a binary MIP in n repeated applications of the technique, where n is...

In order for automated mobile vehicles to navigate in the real world with minimal collision risks, it is necessary their planning algorithms consider uncertainties from measurements and environmental disturbances. this paper, we analytical solutions a conservative approximation of mutual probability between two robotic presence such uncertainties. Therein, present methods, which call unitary sc...

Abstract The optimal operation of the integrated electricity and heat systems (IEHS) can bring environmental benefits, reduce operational cost, achieve high penetration levels renewables. This review aims to provide a comprehensive overview IEHS modeling solution methods for operation. With respect operation, is reviewed from five aspects, including representation dynamic characteristics, flexi...

Quadratic programs (QP) with an indefinite Hessian matrix arise naturally in some direct optimal control methods, e.g. as subproblems in a sequential quadratic programming (SQP) scheme. Typically, the Hessian is approximated with a positive definite matrix to ensure having a unique solution; such a procedure is called regularization. We present a novel regularization method tailored for QPs wit...