A stochastic evolution algorithm for the graph covering problem and its application to the technology mapping

A stochastic evolution algorithm is applied to solve the graph covering problem in which a set of patterns that fully covers a subject graph with a minimal cost is sought. This problem is a typical constrained combinatorial optimization problem and is proven to be NP-complete. Many branch-and-bound...

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Bibliographic Details
Published in:Proceedings of 1996 IEEE International Conference on Evolutionary Computation (ICEC '96): May 20-22, 1996, Symposion & Toyoda Auditorium, Nagoya University, Japan pp. 475 - 479
Main Authors: Dae-Hyun Lee, Hoon Choi, Lae-Jeong Park, Cheol Hoon Park, Seung Ho Hwang
Format: Conference Proceeding
Language:English
Published: IEEE 1996
Subjects:
Business continuity
Encoding
Heuristic algorithms
Libraries
Logic circuits
Pattern matching
Space technology
Stochastic processes
Tree graphs
Very large scale integration
ISBN:9780780329027, 0780329023
Online Access:Get full text
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Summary:A stochastic evolution algorithm is applied to solve the graph covering problem in which a set of patterns that fully covers a subject graph with a minimal cost is sought. This problem is a typical constrained combinatorial optimization problem and is proven to be NP-complete. Many branch-and-bound algorithms with different heuristics have been proposed but most of them cannot handle practical sized problems like the technology mapping problem from the VLSI synthesis area. Our stochastic evolution is based on a problem-specific encoding scheme to reduce the size of the search space and incorporates the tree matching algorithm at the initial solution generation stage for speed-up. Experimental results show that the proposed algorithm produces good solutions within a reasonable amount of time.
ISBN:9780780329027
0780329023
DOI:10.1109/ICEC.1996.542647