Sökning: "unconstrained optimization"

Visar resultat 1 - 5 av 17 avhandlingar innehållade orden unconstrained optimization.

1. 1. Asynchronous Algorithms for Large-Scale Optimization : Analysis and Implementation

   Författare :Arda Aytekin; Mikael Johansson; Panagiotis K. Patrinos; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; convex optimization; optimization; asynchronous algorithms; algorithms; parallel algorithms; large-scale; big data; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : This thesis proposes and analyzes several first-order methods for convex optimization, designed for parallel implementation in shared and distributed memory architectures. The theoretical focus is on designing algorithms that can run asynchronously, allowing computing nodes to execute their tasks with stale information without jeopardizing convergence to the optimal solution. LÄS MER

3. 2. On Methods for Solving Symmetric Systems of Linear Equations Arising in Optimization

   Författare :Tove Odland; Anders Forsgren; William W. Hager; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; symmetric system of linear equations; method of conjugate gradients; quasi-Newton method; unconstrained optimization; unconstrained quadratic optimiza- tion; Krylov subspace method; unnormalized Lanczos vectors; minimum-residual method; symmetriska linjära ekvationssystem; konjugerade gradientmetoden; kvasi- Newtonmetoder; optimering utan bivillkor; kvadratisk optimering utan bivillkor; Kry- lovunderrumsmetoder; icke-normaliserade Lanczosvektorer; minimum-residualmetoden; Mathematics; Matematik;

   Sammanfattning : In this thesis we present research on mathematical properties of methods for solv- ing symmetric systems of linear equations that arise in various optimization problem formulations and in methods for solving such problems.In the first and third paper (Paper A and Paper C), we consider the connection be- tween the method of conjugate gradients and quasi-Newton methods on strictly convex quadratic optimization problems or equivalently on a symmetric system of linear equa- tions with a positive definite matrix. LÄS MER

4. 3. Approaches to accelerate methods for solving systems of equations arising in nonlinear optimization

   Författare :David Ek; Anders Forsgren; Jacek Gondzio; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Nonlinear optimization; mathematical programming; interior-point methods; approximate solutions to systems of linear equations; method of conjugate gradients; quasi-Newton methods; modified Newton methods; Ickelinjär optimering; matematisk programmering; inre-punktsmetoder; approximativa lösningar till linjära ekvationssystem; konjugerade gradientmetoden; kvasi-Newtonmetoder; modifierade Newtonmetoder.; Optimization and Systems Theory; Optimeringslära och systemteori;

   Sammanfattning : Methods for solving nonlinear optimization problems typically involve solving systems of equations. This thesis concerns approaches for accelerating some of those methods. In our setting, accelerating involves finding a trade-off between the computational cost of an iteration and the quality of the computed search direction. LÄS MER

5. 4. Applications of Integer Quadratic Programming in Control and Communication

   Författare :Daniel Axehill; Anders Hansson; Anders Rantzer; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Optimization; Model Predictive Control; CDMA; Quadratic Programming; Mixed Integer Quadratic Programming; Dual active set methods; Riccati recursion; Branch and bound; Automatic control; Reglerteknik;

   Sammanfattning : The main topic of this thesis is integer quadratic programming with applications to problems arising in the areas of automatic control and communication. One of the most widespread modern control principles is the discrete-time method Model Predictive Control (MPC). LÄS MER

7. 5. Structure-Exploiting Numerical Algorithms for Optimal Control

   Författare :Isak Nielsen; Daniel Axehill; Anders Hansson; Eric Kerrigan; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Numerical Optimal Control; Model Predictive Control; Riccati Recursion; Parallel Algorithms; Low-Rank Modifications; Parametric Programming; Optimization; Explicit MPC; Moving Horizon Estimation; Partial Condensing;

   Sammanfattning : Numerical algorithms for efficiently solving optimal control problems are important for commonly used advanced control strategies, such as model predictive control (MPC), but can also be useful for advanced estimation techniques, such as moving horizon estimation (MHE). In MPC, the control input is computed by solving a constrained finite-time optimal control (CFTOC) problem on-line, and in MHE the estimated states are obtained by solving an optimization problem that often can be formulated as a CFTOC problem. LÄS MER