Improving complex SMT strategies with learning-Reference-Cited by-同舟云学术

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Improving complex SMT strategies with learning

Published:2019-03-15 Issue:2 Volume:27 Page:1162-1188
ISSN:0969-6016
Container-title:International Transactions in Operational Research
language:en
Short-container-title:Intl. Trans. in Op. Res.

Author:

Gálvez Ramírez Nicolás¹²,Monfroy Eric³^ORCID,Saubion Frédéric²^ORCID,Castro Carlos¹

Affiliation:

1. LabDII, Departamento de InformíticaUniversidad Técnica Federico Santa María 1680, Av. España Valparaíso Chile

2. Laboratoire d'Etude et de Recherche en Informatique d'AngersLERIA, EA 2645, SFR MathSTIC, UNIV Angers, Faculté des Sciences, 2 Bd Lavoisier 49045 Angers France

3. LS2N, UMR CNRS 6004, Université de Nantes, UFR de Sciences et Techniques2 rue de la Houssiniére BP 92208, 44322 Nantes cedex 03 France

Publisher

Wiley

Subject

Management of Technology and Innovation,Management Science and Operations Research,Strategy and Management,Computer Science Applications,Business and International Management

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/itor.12650

Reference30 articles.

1. Evolutionary Algorithms in Theory and Practice

2. CVC4

3. 6 Years of SMT-COMP

4. Barrett C. Fontaine P. Tinelli C. 2015.The SMT‐LIB standard: version 2.5. Technical report Department of Computer Science The University of Iowa Iowa City IA.

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