Sökning: "Global Optimization"
Visar resultat 16 - 20 av 291 avhandlingar innehållade orden Global Optimization.
16. Global Shape Description of Digital Objects
Sammanfattning : New methods for global shape description of three-dimensional digital objects are presented. The shape of an object is first represented by a digital surface where the faces are either triangles or quadrilaterals. LÄS MER
17. Copula-based Portfolio Optimization
Sammanfattning : This thesis studies and develops copula-based portfolio optimization. The overall purpose is to clarify the effects of copula modeling for portfolio allocation andsuggest novel approaches for copula-based optimization. The thesis is a compilation of five papers. LÄS MER
18. Fast local optimization in decision analytic software
Sammanfattning : In decision analysis, significant recognition has been given to the fact that requiring numerically precise information seems unrealistic for real-life decision situations, Despite the emergence of many modern apporaches, which attempt to handle imprecise estimates, concentration has focused more on representation and less on evaluation. Methods such as the DELTA method challenged this issue by its evaluation framework that can accommodate both precision an imprecision, and thus pushes forward the disign of advanced dicision analysis systems. LÄS MER
19. Distributed Optimization with Nonconvexities and Limited Communication
Sammanfattning : In economical and sustainable operation of cyber-physical systems, a number of entities need to often cooperate over a communication network to solve optimization problems. A challenging aspect in the design of robust distributed solution algorithms to these optimization problems is that as technology advances and the networks grow larger, the communication bandwidth used to coordinate the solution is limited. LÄS MER
20. Accelerating Convergence of Large-scale Optimization Algorithms
Sammanfattning : Several recent engineering applications in multi-agent systems, communication networks, and machine learning deal with decision problems that can be formulated as optimization problems. For many of these problems, new constraints limit the usefulness of traditional optimization algorithms. LÄS MER