A review of literature on parallel constraint solving
As multi-core computing is now standard, it seems irresponsible for constraints researchers
to ignore the implications of it. Researchers need to address a number of issues to exploit …
to ignore the implications of it. Researchers need to address a number of issues to exploit …
[HTML][HTML] Conjure: Automatic generation of constraint models from problem specifications
When solving a combinatorial problem, the formulation or model of the problem is critical to
the efficiency of the solver. Automating the modelling process has long been of interest …
the efficiency of the solver. Automating the modelling process has long been of interest …
Progress towards the holy grail
EC Freuder - Constraints, 2018 - Springer
Progress towards the Holy Grail | SpringerLink Skip to main content Advertisement
SpringerLink Log in Menu Find a journal Publish with us Search Cart 1.Home 2.Constraints …
SpringerLink Log in Menu Find a journal Publish with us Search Cart 1.Home 2.Constraints …
[HTML][HTML] Automated streamliner portfolios for constraint satisfaction problems
Constraint Programming (CP) is a powerful technique for solving large-scale combinatorial
problems. Solving a problem proceeds in two distinct phases: modelling and solving …
problems. Solving a problem proceeds in two distinct phases: modelling and solving …
Instance generation via generator instances
Access to good benchmark instances is always desirable when developing new algorithms,
new constraint models, or when comparing existing ones. Hand-written instances are of …
new constraint models, or when comparing existing ones. Hand-written instances are of …
Closed frequent itemset mining with arbitrary side constraints
Frequent itemset mining (FIM) is a method for finding regularities in transaction databases. It
has several application areas, such as market basket analysis, genome analysis, and drug …
has several application areas, such as market basket analysis, genome analysis, and drug …
Automatic generation and selection of streamlined constraint models via monte carlo search on a model lattice
Streamlined constraint reasoning is the addition of uninferred constraints to a constraint
model to reduce the search space, while retaining at least one solution. Previously it has …
model to reduce the search space, while retaining at least one solution. Previously it has …
Towards portfolios of streamlined constraint models: a case study with the balanced academic curriculum problem
Augmenting a base constraint model with additional constraints can strengthen the
inferences made by a solver and therefore reduce search effort. We focus on the automatic …
inferences made by a solver and therefore reduce search effort. We focus on the automatic …
Automatic streamlining for constrained optimisation
Augmenting a base constraint model with additional constraints can strengthen the
inferences made by a solver and therefore reduce search effort. We focus on the automatic …
inferences made by a solver and therefore reduce search effort. We focus on the automatic …
Modelling langford's problem: a viewpoint for search
The performance of enumerating all solutions to an instance of Langford's Problem is
sensitive to the model and the search strategy. In this paper we compare the performance of …
sensitive to the model and the search strategy. In this paper we compare the performance of …