Exploiting symmetries within constraint satisfaction search
Symmetry often appears in real-world constraint satisfaction problems, but strategies for exploiting it are only beginning to be developed. Here, a framework for exploiting symmetry within depth-first search is proposed, leading to two heuristics for variable selection and a domain pruning procedure...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2001 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/30530 |
| Acceso en línea: | http://hdl.handle.net/10261/30530 |
| Access Level: | acceso abierto |
| Palabra clave: | Symmetry Constraint satisfaction Heuristics Nogoods Robots |
| Sumario: | Symmetry often appears in real-world constraint satisfaction problems, but strategies for exploiting it are only beginning to be developed. Here, a framework for exploiting symmetry within depth-first search is proposed, leading to two heuristics for variable selection and a domain pruning procedure. These strategies are then applied to two highly symmetric combinatorial problems, namely the Ramsey problem and the generation of balanced incomplete block designs. Experimental results show that these general-purpose strategies can compete with, and in some cases outperform, previous more ad hoc procedures. |
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