Specializing narrowing for timetable generation: a case study

Authors:
Nadia Brauner;Rachid Echahed;Gerd Finke;Hanns Gregor;Frederic Prost
Affiliations:
Institut d’Informatique et de Mathématiques Appliquées de Grenoble, Laboratoire Leibniz, Grenoble, France;Institut d’Informatique et de Mathématiques Appliquées de Grenoble, Laboratoire Leibniz, Grenoble, France;Institut d’Informatique et de Mathématiques Appliquées de Grenoble, Laboratoire Leibniz, Grenoble, France;Institut d’Informatique et de Mathématiques Appliquées de Grenoble, Laboratoire Leibniz, Grenoble, France;Institut d’Informatique et de Mathématiques Appliquées de Grenoble, Laboratoire Leibniz, Grenoble, France
Venue:
PADL'05 Proceedings of the 7th international conference on Practical Aspects of Declarative Languages
Year:
2005

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Abstract

An important property of strategies used to solve goals in functional logic programming (FLP) languages is the complete exploration of the solution space. Integrating constraints into FLP proved to be useful in many cases, as the resulting constraint functional logic programming (CFLP) offers more facilities and more efficient operational semantics. CFLP can be achieved by means of conditional rewrite systems with a narrowing-based operational semantics. A common idea to improve the efficiency of such operational semantics is to use specific algorithms from operations research as constraint solvers. If the algorithm does not return a complete set of solutions, the property of completeness might be lost. We present a real world timetabling problem illustrating this approach. We propose an algorithm, obtained as an integration of three known optimization algorithms for the linear assignment problem (LAP), enumerating solutions to the LAP in order of increasing weight, such that resolution of goals is complete again. We show, how the narrowing process can be tailored to use this algorithm and provide an efficient way to solve the timetable generation problem.