Constraint satisfaction

Dobson, J. F., Dinte, B. P, 1996, Constraint Satisfaction in Local and Gradient Susceptibility Approximations Application to a Van der Waals Density Functional , Phys. Rev. Lett., 16, 1780. 

R. Bejar, B. Krishnamachari, C. Gomes, and B. Selman, Distributed constraint satisfaction in a wireless sensor tracking system , in Proceedings of the Workshop on Distributed Constraint Reasoning, International Joint Conference on Artificial Intelligence, Seattle, USA, August 2001. 

J. P. Perdew, A. Ruzsinszky, J. M. Tao, V. N. Staroverov, G. E. Scuseria, and G. I. Csonka, Prescription for the Design and Selection of Density Functional Approximations More Constraint Satisfaction with Fewer Fits, J. Chem. Phys. 123 (2005), 062201. 

The nominal profit (case 1) is somewhat higher than that in Table 9.7. This is due to variation of reflux ratio over the batch time. Also in contrast to previous scheme (case 2 of Table 9.7) little loss of nominal performance is entailed in robustly satisfying the constraints. The temperature trajectory of case 2 shown in Figure 9.17 is qualitatively similar to the nominal optimum policy, but has been modified slightly to ensure constraint satisfaction. 

Perdew JP, Ruzsinsky A, Tao J, Starovyerov V, Scuseria GE, Csonka GI (2005) Prescription for the design and selection of density functional approximations More constraint satisfaction with... 

Zhao, Y Schultz, N. E. Truhlar, D. G. Design of density functionals by combining the method of constraint satisfaction with parametrization for thermochemistry, thermochemical kinetics, and noncovalent interactions, 7. Chem. Theory Comput. 2006, 2, 364-382. 

The on-line optimization problem is nonlinear and involves equahty constraints. Satisfaction of those constraints is not exact, but approximate (within e). 

The design variables are chosen to allow constraint satisfaction for all the uncertain variable values while the operating variables are adjusted for each value of the uncertain variables. If operating variables are eliminated, the problem simplifies to... 

The objective of phase 2, in particular, is the selection of the most suitable compound for constraint satisfaction. We want to given priority to compounds that participate (as reactants or products) in only a small number of pathways that are active in the current state of the problem. 

R. B. Altman and J. F. Brinkley. 1993. Probabilistic constraint satisfaction with structural models Application to organ modeling by radial contours. In Proceedings, 17th Symposium on Computer Applications in Medical Care. Washington, DC, pp. 492 197. 

Constraint satisfaction. A more successful approach consists in designing functionals of the form... 

Purely empirical functionals often work well, because satisfaction of many secondary constraints (the uniform, high- and low-density limits, density scaling transformations, and so on) is not essential for a good performance for usual properties ( molecules do not behave like the UEG ). The price for avoiding the hard work of constraint satisfaction is that optimized functionals may fail badly in situations for which they were not trained . 

Hentemyck P.V. 1989. Constraint Satisfaction in Logic Programming. MIT Press, Cambridge, MA. 

Hooker J. 2000. Logic Based Methods for Optimization Combining Optimization and Constraint Satisfaction. John Wiley and Sons Inc., New York. 

Nuijten W.P.M. 1994. Time and resource constrained schednling A constraint satisfaction approach. Ph.D. Thesis, Eindhoven University of Technology. 

Constraint satisfaction deals with problems defined over finite domains. A constraint satisfaction problem is defined as follows ... 

A solution for a constraint satisfaction problem is a set of assignments of values from its domain to every variable so that all constraints are satisfied at once. 

---