The Theory and Applications of Discrete Constrained Optimization Using Lagrange Multipliers

Finally, we demonstrate the efficiency and effectiveness of our proposed theory and methods. DLM is able to solve systematically general discrete, continuous and mixed-integer constrained benchmarks, which is a task not achieved by previous methods. DLM has found better multiplierless filter-bank designs that improve over all of Johnston's benchmark designs using a maximum of three to six ONE bits in each filter coefficient instead of using floating-point representations. Finally, DLM has found efficiently new solutions for satisfiability problems that were not possible by existing local- and global search techniques.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Wu, Zhe

Contributors dc:contributor

• Wah, Benjamin W.

• Computer Science

Language dc:language

eng

Identifier

(MiAaPQ)AAI3017257

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81578