Set Variables
Set variable is essential for the modelling of some classes of combinatorial problem. It captures more semantics of the problem than finite domain variables, hence lead to better domain reduction during search. Expressing the domain of set variable is not trivial, existing methods either consume too much space, or is difficult to achieve adaquate level of consistency. This line of research tries to remedy these problems by proposing a domain representation (the Length-Lex set representation) that requires small storage space and allows achieving bound consistency effectively. The empirical evaluation shows that Length-Lex is very robust across a number of standard CSP benchmarks.
- Bound Consistency for Binary Length-Lex Set Constraints. Pascal Van Hentenryck, Justin Yip, Carmen Gervet, and Gregoire Dooms. In Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-08), Chicago, July 2008. (pdf)
- Length-Lex Bound Consistency for Knapsack Constraints. Justin Yip, Pascal Van Hentenryck. In ACM SAC 2009, Hawaii, March 2009. (pdf)
- The Evaluation of Length-Lex Set Variables. Justin Yip, Pascal Van Hentenryck. In CP 2009, Lisbon, Sept 2009. (pdf)
- Length-Lex Set Variables (Poster). Justin Yip. In CP 2009 Doctoral Program, Lisbon, Sept 2009. (pdf)
- Boosting Set Constraint Propagation for Network Design. Justin Yip, Pascal Van Hentenryck, Carmen Gervet. In CPAIOR 2010, Bologna, June 2010. (pdf)
- Exponential Propagation for Set Variables. Justin Yip, Pascal Van Hentenryck. In CP 2010, St. Andrews, Sept 2010. (pdf)
- Exponential Propagation for Set-CSPs. Justin Yip, Pascal Van Hentenryck. Constraints, submitted. (pdf)
- Boosting Network Design with Set Constraint Propagation. Justin Yip, Pascal Van Hentenryck, Carmen Gervet. Constraints, submitted. (pdf)