Principles of constraint programming

By K. Apt. 2003

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Constraint Propagation (2006, background): “It is shown in [2] that we can also enforce higher-order consistencies, such as path consistency, by defining sets of monotonic propagators that involve several constraints at a time and that alter the set of constraints.”
Primal Heuristics for Mixed Integer Programs (2006, methodology): “SCIP [1] is a framework created to solve Constraint Integer Programs, shortly called CIPs, which denotes an integration of Constraint Programming (see for example [7]) and Mixed Integer Programming.”
Review of job shop scheduling research and its new perspectives under Industry 4.0 (2017, background): “More detailed information about constraint satisfaction techniques in different ﬁelds can be found in Apt (2003) and Rossi et al. (2006).”
Constraint Logic Programming (2010, background): “Constraint solving [127, 6, 56, 31] includes a variety of expressive modelling frameworks and efficient solving tools for real-life problems that can be described via a set of variables and constraints over them.”