Sökning: "primal convergence"
Visar resultat 1 - 5 av 16 avhandlingar innehållade orden primal convergence.
1. Conditional Subgradient Methods and Ergodic Convergence in Nonsmooth Optimization
Sammanfattning : The topic of the thesis is subgradient optimization methods in convex, nonsmooth optimization. These methods are frequently used, especially in the context of Lagrangean relaxation of large scale mathematical programs where they are remarkably often able to quickly identify near-optimal Lagrangean dual solutions. LÄS MER
2. Optimization of Maintenance Planning for Multi-Component Systems, and Primal-Dual Convergence Characterizations in Convex Optimization
Sammanfattning : This thesis considers two topics within mathematical programming. The first topic is an investigation into the behaviour of primal-dual subgradient algorithms with primal ergodic averaging in the case where it is not known a priori whether the primal program is consistent or not. LÄS MER
3. Distributed Optimization and Control : Primal--Dual, Online, and Event-Triggered Algorithms
Sammanfattning : In distributed optimization and control, each network node performs local computation based on its own information and information received from its neighbors through a communication network to achieve a global objective. Although many distributed optimization and control algorithms have been proposed, core theoretical problems with important practical relevance remain. LÄS MER
4. A Structure Utilizing Inexact : Primal-Dual Interior-Point Method for Analysis of Linear Differential Inclusions
Sammanfattning : The ability to analyze system properties for large scale systems is an important part of modern engineering. Although computer power increases constantly, there is still need to develop tailored methods that are able to handle large scale systems, since sometimes standard methods cannot handle the large scale problems that occur. LÄS MER
5. Topics in convex and mixed binary linear optimization
Sammanfattning : This thesis concerns theory, algorithms, and applications for two problem classes within the realm of mathematical optimization; convex optimization and mixed binary linear optimization. To the thesis is appended five papers containing its main contributions. LÄS MER