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

Authors:
James Bowen;Gerry Dozier
Affiliations:
Department of Computer Science, National University of Ireland at Cork, Cork, Ireland;NASA Center for Autonomous Control Engineering, Department of Computer Science, North Carolina A&T State University, Greensboro, NC
Venue:
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Year:
1996

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Abstract

This paper introduces a hybrid evolutionary hill-climbing algorithm that quickly solves Constraint. Satisfaction Problems (CSPs). This hyhrid 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.