Portfolio approaches for constraint optimization problems

被引:0
|
作者
Roberto Amadini
Maurizio Gabbrielli
Jacopo Mauro
机构
[1] University of Bologna,Department of Computer Science and Engineering/Lab. Focus INRIA
关键词
Algorithm portfolio; Artificial intelligence; Combinatorial optimization; Constraint programming; Machine learning; 90C27;
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学科分类号
摘要
Within the Constraint Satisfaction Problems (CSP) context, a methodology that has proven to be particularly performant consists of using a portfolio of different constraint solvers. Nevertheless, comparatively few studies and investigations have been done in the world of Constraint Optimization Problems (COP). In this work, we provide a generalization to COP as well as an empirical evaluation of different state of the art existing CSP portfolio approaches properly adapted to deal with COP. The results obtained by measuring several evaluation metrics confirm the effectiveness of portfolios even in the optimization field, and could give rise to some interesting future research.
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页码:229 / 246
页数:17
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