NDLI: Set constraint model and automated encoding into SAT: application to the social golfer problem

Content Provider	Springer Nature Link
Author	Lardeux, Frédéric Monfroy, Eric Crawford, Broderick Soto, Ricardo
Copyright Year	2015
Abstract	On the one hand, constraint satisfaction problems allow one to expressively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to expressively model set constraint problems and to encode them automatically into SAT instances. We apply our technique to the social golfer problem and we also use it to break symmetries of the problem. Our technique is simpler, more expressive, and less error-prone than direct modeling. The SAT instances that we automatically generate contain less clauses than improved direct instances such as in Triska and Musliu (Ann Oper Res 194(1):427–438, 2012), and with unit propagation they also contain less variables. Moreover, they are well-suited for SAT solvers and they are solved faster as shown when solving difficult instances of the social golfer problem.
Starting Page	423
Ending Page	452
Page Count	30
File Format	PDF
ISSN	02545330
Journal	Annals of Operations Research
Volume Number	235
Issue Number	1
e-ISSN	15729338
Language	English
Publisher	Springer US
Publisher Date	2015-06-09
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Constraint programming CSP Set constraints SAT encoding Social golfer problem Operation Research/Decision Theory Combinatorics Theory of Computation
Content Type	Text
Resource Type	Article
Subject	Management Science and Operations Research

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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