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Showing 1 to 9 of 9 for “"Nonsmooth optimization"”.

  1. Distributed cooperative trajectory generation for multiple autonomous vehicles using Pythagorean Hodograph Bézier curves

    … problem, that falls under the class of nonsmooth optimization problems. The proposed distributed algorithm combines the bundle method, a widely used solver for nonsmooth optimization problems, with a distributed nonlinear programming method. In the latter, a distributed formulation is …

    uiuc Repository record for Distributed cooperative trajectory generation for multiple autonomous vehicles using Pythagorean Hodograph Bézier curves (opens in a new tab)

  2. Nonsmooth dynamic optimization of systems with varying structure

    In this thesis, an open-loop numerical dynamic optimization method for a class of dynamic systems is developed. The structure of the governing equations of the systems under consideration change depending on the values of the states, parameters and the controls. Therefore, these systems are called …

    mit Repository record for Nonsmooth dynamic optimization of systems with varying structure (opens in a new tab)

  3. Full Stability In Optimization

    … a systematic study of full stability in general optimization models including its conventional Lipschitzian version as well as the new Holderian one. We derive various characterizations of both Lipschitzian and Holderian full stability in nonsmooth optimization, which are new in …

    wayne-thes Repository record for Full Stability In Optimization (opens in a new tab)

  4. Learning-based optimal and robust control: A policy optimization perspective

    … robotic tasks. Central to this success is policy optimization (PO), a subclass of RL where policies—parameterized mappings from observations to actions—are iteratively optimized to enhance system performance. PO’s flexibility, scalability, and data-driven nature make it effective for tackling …

    uiuc Repository record for Learning-based optimal and robust control: A policy optimization perspective (opens in a new tab)

  5. Efficient Numerical Algorithms for Structured Nonsmooth Min–Max and Adjustable Robust Optimization problems with Applications

    In this thesis, we consider structured nonsmooth optimization problems whose objective function and/or the functions describing the constraints can be expressed as the maximum of a collection of auxiliary functions in a lifted space over a parameter set. This class of problems arises in important …

    unsw Repository record for Efficient Numerical Algorithms for Structured Nonsmooth Min–Max and Adjustable Robust Optimization problems with Applications (opens in a new tab)

  6. ΥΠΟΛΟΓΙΣΜΟΣ ΦΟΡΕΩΝ ΜΕ ΔΙΕΠΙΦΑΝΕΙΕΣ. ΜΟΡΦΩΣΗ ΚΑΙ ΜΕΛΕΤΗ ΠΡΟΒΛΗΜΑΤΩΝ ΑΝΙΣΟΤΗΤΩΝ ΜΕΤΑΒΟΛΩΝ-ΗΜΙΜΕΤΑΒΟΛΩΝ

    … IS STUDIED IN THE FRAMEWORK OF INEQUALITY (NONSMOOTH) MECHANICS. MONOTONE AND NONMONOTONE, POSSIBLYMULTIVALUED INTERFACE LAWS CAN BE PRODUCED FROM APPROPRIATELY DEFINED CONVEX AND NONCONVEX, GENERALLY NONDIFFERENTIABLE SUPERPOTENTIALS BY MEANS OF GENERALIZATIONS OF THE DIFFERENTIAL NOTION OF …

    greece Repository record for ΥΠΟΛΟΓΙΣΜΟΣ ΦΟΡΕΩΝ ΜΕ ΔΙΕΠΙΦΑΝΕΙΕΣ. ΜΟΡΦΩΣΗ ΚΑΙ ΜΕΛΕΤΗ ΠΡΟΒΛΗΜΑΤΩΝ ΑΝΙΣΟΤΗΤΩΝ ΜΕΤΑΒΟΛΩΝ-ΗΜΙΜΕΤΑΒΟΛΩΝ (opens in a new tab)

  7. Accelerated first-order optimization methods using inertia and error bounds

    Optimization is an important discipline of applied mathematics with far-reaching applications. Optimization algorithms often form the backbone of practical systems in machine learning, image processing, signal processing, computer vision, data analysis, and statistics. In an age of massive data …

    uiuc Repository record for Accelerated first-order optimization methods using inertia and error bounds (opens in a new tab)

  8. Mathematical analysis of a dynamical system for sparse recovery

    … and can be accomplished by solving a complex optimization program. While many solvers have been proposed and analyzed to solve such programs in digital, their high complexity currently prevents their use in real-time applications. On the contrary, a continuous-time neural network implemented …

    gatech Repository record for Mathematical analysis of a dynamical system for sparse recovery (opens in a new tab)

  9. Composite Minimization: Proximity Algorithms and Their Applications

    … and compressed sensing, are often modeled as nonsmooth optimization</p> <p>problems whose objective functions are the sum of two terms, each of which is the</p> <p>composition of a prox-friendly function with a matrix. Therefore, there is a practical</p> <p>need to solve such optimization

    syracuse-diss Repository record for Composite Minimization: Proximity Algorithms and Their Applications (opens in a new tab)