Combinatorial optimization by stochastic evolution with applications to the physical design of VLSI circuits

In this thesis, a new general adaptive algorithm for solving a wide variety of NP-Complete combinatorial problems is developed. The new technique is called Stochastic Evolution (SE). The SE algorithm is applied to Network Bisection, Vertex Cover, Set Partition, Hamilton Circuit, Traveling Salesman, Linear Ordering, Standard Cell Placement, and Multi-way Circuit Partitioning problems. It is empirically shown that SE out-performs the more established general optimization algorithm, namely, Simulated Annealing.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Saab, Youssef Georges

Contributors dc:contributor

• Rao, Vasant B.

• Engineering, Electronics and Electrical
• Computer Science

Statement dc:rights

• Copyright 1990 Saab, Youssef Georges

Language dc:language

eng

Identifier

AAI9114396
(UMI)AAI9114396

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/19695