Parallel hierarchical methods for complex systems optimization

Authors:
Ewa Niewiadomska-Szynkiewicz
Affiliations:
Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, Poland
Venue:
ICCSA'06 Proceedings of the 6th international conference on Computational Science and Its Applications - Volume Part I
Year:
2006

Citing 5
Cited 0

Hierarchical multiobjective analysis for large-scale systems: reviews and current status

Automatica (Journal of IFAC)
Optimization flow control—I: basic algorithm and convergence

IEEE/ACM Transactions on Networking (TON)
Markowitz Revisited: Mean-Variance Models in Financial Portfolio Analysis

SIAM Review
The Mathematics of Internet Congestion Control (Systems and Control: Foundations and Applications)

The Mathematics of Internet Congestion Control (Systems and Control: Foundations and Applications)
Optimization network flow control and price coordination with feedback: proposal of a new distributed algorithm

Computer Communications

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper is concerned with computational research for large scale systems. The focus is on the hierarchical optimization methods that can be successfully applied to large scale optimization problems. A key issue is the possibility of solving several less dimension problems instead of one global high dimension task. Particular emphasis is laid on coarse granularity parallel implementation and its effectiveness. The paper discusses the usage of price coordination for real-life systems optimization. The results of numerical experiments performed for mean-variance portfolio selection using cluster of computers are presented and discussed.