Trends in constraint programming /
edited by Frederic Benhamou, Narendra Jussien, Barry O'Sullivan.
- Newport Beach, CA : ISTE USA, 2007.
- 1 online resource (408 pages) : illustrations
Includes bibliographical references and index.
Trends in Constraint Programming; Contents; Introduction; Part I. The Past, Present and Future of Constraint Programming; Chapter 1. Constraint Programming as Declarative Algorithmics; 1.1. The CHIP project; 1.2. The Numerica project; 1.3. The OPL project; 1.4. The Comet project; 1.5. The future of constraint programming; Chapter 2. Constraint Programming Tools; 2.1. Introduction; 2.2. Invited talks; 2.2.1. The development of an industrial CP tool; 2.2.1.1. Design goals; 2.2.1.2. The future; 2.2.2. System design: taking informed decisions; 2.2.2.1. Search; 2.2.2.2. Constraint propagation 2.2.2.3. Variables2.3. System presentations; 2.3.1. ECLiPSe; 2.3.2. SICStus FD; 2.3.3. G12; 2.3.4. DiSolver; 2.3.5.MINION; 2.3.6. Choco; 2.3.7. Gecode; 2.3.8. Comet; 2.3.9. JaCoP; 2.3.10. Borderwijk; 2.4. Panels; 2.5. Conclusion; 2.6. References; Chapter 3. The Next 10 Years of Constraint Programming; 3.1. Pedro Barahona; 3.2. Christian Bessiere; 3.3. Peter Jeavons; 3.4. Pedro Meseguer; 3.5. Gilles Pesant; 3.6. Francesca Rossi; 3.7. Thomas Schiex; 3.8. Christian Schulte; 3.9. Meinolf Sellmann; 3.10. Mark Wallace; 3.11. Toby Walsh; 3.12. Roland Yap; 3.13. References 4.6. A new filtering algorithm for the graph isomorphism problem4.6.1. A global constraint for the graph isomorphism problem; 4.6.2. ILL-consistency and ILL-filtering; 4.6.3. Experimental results; 4.7. References; Chapter 5. On the First SAT/CP Integration Workshop; 5.1. The technical program; 5.1.1. The invited talk; 5.1.2. Contributions related to SMT and solver integration; 5.1.3. Contributions related to the use of SAT techniques to improve CSP/CP solvers; 5.1.4. Other contributions; 5.2. The panel session; 5.2.1. Are SAT and CP different or similar? 5.2.2. Why has SAT succeeded in reducing the tuning issue?5.2.3. How long can the current generation of SAT solvers evolve?; 5.2.4. Were performance issues correctly addressed by CP?; 5.2.5. Was CP too ambitious?; 5.2.6. Do we still need CP?; 5.3. Summary, future directions and conclusion; 5.4. References; Chapter 6. Constraint-Based Methods for Bioinformatics; 6.1. On using temporal logic with constraints to express biological properties of cell processes; 6.2. Modeling biological systems in stochastic concurrent constraint programming
Constraint programming is a constantly evolving field, something which is explored at the annual International Conference on Principles and Practice of Constraint Programming. This conference provides papers and workshops which produce new insights, concepts and results which those involved in this area can then use to develop their own work. This title provides an accessible overview of this by bringing together the best papers on a range of topics within this subject area, thus allowing those involved in constraint programming to benefit from the new innovations and results created as a res.