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

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,...

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Bibliographic Details
Main Author: Saab, Youssef Georges
Format: Dissertation
Language:English
Published: ProQuest Dissertations & Theses 01-01-1990
Subjects:
Computer science
Electrical engineering
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Summary: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.
ISBN:9798207821245