Constraint satisfaction using a hybrid evolutionary hill-climbing algorithm that performs opportunistic arc and path revision

Conference · Tue Dec 31 00:00:00 EST 1996

OSTI ID:430675

Bowen, J ^[1]; Dozier, G ^[2]

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1. National Univ. of Ireland, Cork (Ireland)
2. North Carolina A&T State Univ., Greensboro, NC (United States)

This paper introduces a hybrid evolutionary hill-climbing algorithm that quickly solves (Constraint Satisfaction Problems (CSPs)). This hybrid uses opportunistic arc and path revision in an interleaved fashion to reduce the size of the search space and to realize when to quit if a CSP is based on an inconsistent constraint network. This hybrid outperforms a well known hill-climbing algorithm, the Iterative Descent Method, on a test suite of 750 randomly generated CSPs.

• OSTI ID: 430675
• Report Number(s): CONF-960876-; TRN: 96:006521-0050
• Resource Relation: Conference: 13. National conference on artifical intelligence and the 8. Innovative applications of artificial intelligence conference, Portland, OR (United States), 4-8 Aug 1996; Other Information: PBD: 1996; Related Information: Is Part Of Proceedings of the thirteenth national conference on artificial intelligence and the eighth innovative applications of artificial intelligence conference. Volume 1 and 2; PB: 1626 p.
• Country of Publication: United States
• Language: English

Related Subjects

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