Essence

Essence: A constraint language for specifying combinatorial problems. Essence is a formal language for specifying combinatorial problems in a manner similar to natural rigorous specifications that use a mixture of natural language and discrete mathematics. Essence provides a high level of abstraction, much of which is the consequence of the provision of decision variables whose values can be combinatorial objects, such as tuples, sets, multisets, relations, partitions and functions. Essence also allows these combinatorial objects to be nested to arbitrary depth, providing for example sets of partitions, sets of sets of partitions, and so forth. Therefore, a problem that requires finding a complex combinatorial object can be specified directly by using a decision variable whose type is precisely that combinatorial object.


References in zbMATH (referenced in 19 articles , 1 standard article )

Showing results 1 to 19 of 19.
Sorted by year (citations)

  1. Audemard, Gilles; Boussemart, Frédéric; Lecoutre, Christophe; Piette, Cédric; Roussel, Olivier: XCSP(^3) and its ecosystem (2020)
  2. Belle, Vaishak; De Raedt, Luc: Semiring programming: a semantic framework for generalized sum product problems (2020)
  3. Freuder, Eugene C.: Progress towards the Holy Grail (2018)
  4. Gent, Ian P.; Miguel, Ian; Nightingale, Peter; McCreesh, Ciaran; Prosser, Patrick; Moore, Neil C. A.; Unsworth, Chris: A review of literature on parallel constraint solving (2018)
  5. Schiendorfer, Alexander; Knapp, Alexander; Anders, Gerrit; Reif, Wolfgang: MiniBrass: soft constraints for MiniZinc (2018)
  6. Guns, Tias; Dries, Anton; Nijssen, Siegfried; Tack, Guido; De Raedt, Luc: MiningZinc: a declarative framework for constraint-based mining (2017)
  7. Hemmi, David; Tack, Guido; Wallace, Mark: Scenario-based learning for stochastic combinatorial optimisation (2017)
  8. Amadini, Roberto; Gabbrielli, Maurizio; Mauro, Jacopo: Why CP portfolio solvers are (under)utilized? issues and challenges (2015)
  9. Bruynooghe, Maurice; Blockeel, Hendrik; Bogaerts, Bart; De Cat, Broes; De Pooter, Stef; Jansen, Joachim; Labarre, Anthony; Ramon, Jan; Denecker, Marc; Verwer, Sicco: Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems with IDP3 (2015)
  10. Ansótegui, Carlos; Bofill, Miquel; Palahí, Miquel; Suy, Josep; Villaret, Mateu: Solving weighted CSPs with meta-constraints by reformulation into satisfiability modulo theories (2013)
  11. Heinz, Stefan; Schulz, Jens; Beck, J. Christopher: Using dual presolving reductions to reformulate cumulative constraints (2013)
  12. Bofill, Miquel; Palahí, Miquel; Suy, Josep; Villaret, Mateu: Solving constraint satisfaction problems with SAT modulo theories (2012)
  13. Tasharrofi, Shahab; Ternovska, Eugenia: A semantic account for modularity in multi-language modelling of search problems (2011)
  14. Fages, François; Martin, Julien: From rules to constraint programs with the Rules2CP modelling language (2009)
  15. Järvisalo, Matti; Oikarinen, Emilia; Janhunen, Tomi; Niemelä, Ilkka: A module-based framework for multi-language constraint modeling (2009)
  16. Järvisalo, Matti; Oikarinen, Emilia; Janhunen, Tomi; Niemelä, Ilkka: A module-based framework for multi-language constraint modeling (2009)
  17. Frisch, Alan M.; Harvey, Warwick; Jefferson, Chris; Martínez-Hernández, Bernadette; Miguel, Ian: Essence: A constraint language for specifying combinatorial problems (2008)
  18. Marriott, Kim; Nethercote, Nicholas; Rafeh, Reza; Stuckey, Peter J.; Garcia de la Banda, Maria; Wallace, Mark: The design of the zinc modelling language (2008)
  19. Mitchell, David G.; Ternovska, Eugenia: Expressive power and abstraction in Essence (2008)