Interactively Solving School Timetabling Problems Using Extensions of Constraint Programming

Timetabling problems have been frequently studied due to their wide range of applications. However, they are often solved manually because of the lack of appropriate computer tools. Although many approaches mainly based on local search or constraint programming seem to have been quite successful in recent years, they are often dedicated to specific problems and encounter difficulties in dealing with the dynamic and over-constrained nature of such problems. We were confronted with such an over-constrained and dynamic problem in our institution. This paper deals with a timetabling system based on constraint programming with the use of explanations to offer a dynamic behaviour and to allow automatic relaxations of constraints. Our tool has successfully answered the needs of the current planner by providing solutions in a few minutes instead of a week of manual design. We present in this paper the techniques used, the results obtained and a discussion on the effects of the automation of the timetabling process.

[1]  Narendra Jussien.  E-constraints: Explanation-based constraint programming , 2001 .

[2]  Jean-Charles Régin,et al.  A Filtering Algorithm for Constraints of Difference in CSPs , 1994, AAAI.

[3]  Francesca Rossi,et al.  Constraint Retraction in CLP(FD): Formal Framework and Performance Results , 1999, Constraints.

[4]  Jan Maluszy¿ski,et al.  Best-first search for property maintenance in reactive constraints systems , 1997 .

[5]  François Laburthe,et al.  Challenging explanations for global constraints , 2003 .

[6]  Narendra Jussien,et al.  User-friendly explanations for constraint programming , 2001, WLPE.

[7]  Eddie Cheng,et al.  Flow Formulations for the Student Scheduling Problem , 2002, PATAT.

[8]  Christian Bessiere,et al.  Arc-Consistency in Dynamic Constraint Satisfaction Problems , 1991, AAAI.

[9]  Guillaume Rochart.  Explanations for Global Constraints , 2003, CP.

[10]  Henri Beringer,et al.  Intelligent Backtracking for CLP Languages: An Application to CLP(R) , 1991, ISLP.

[11]  Alan Borning,et al.  Hierarchical Constraint Logic Programming , 1994, J. Log. Program..

[12]  Narendra Jussien,et al.  Local search with constraint propagation and conflict-based heuristics , 2000, Artif. Intell..

[13]  Sancho Salcedo-Sanz,et al.  A two-phase heuristic evolutionary algorithm for personalizing course timetables: a case study in a Spanish university , 2005, Comput. Oper. Res..

[14]  Bertrand Neveu,et al.  Arc-Consistency for Dynamic Constraint Problems: An RMS-Free Approach , 1994 .

[15]  Roman Barták,et al.  Minimal Perturbation Problem in Course Timetabling , 2004, PATAT.

[16]  Narendra Jussien,et al.  Stable solutions for dynamic project scheduling problems , 2004 .

[17]  Jean-Charles Régin,et al.  Generalized Arc Consistency for Global Cardinality Constraint , 1996, AAAI/IAAI, Vol. 1.

[18]  A. Hertz.  Tabu search for large scale timetabling problems , 1991 .

[19]  Romuald Debruyne,et al.  Arc-consistency in dynamic CSPs is no more prohibitive , 1996, Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence.

[20]  Roman Barták,et al.  A New Approach to Modeling and Solving Minimal Perturbation Problems , 2003, CSCLP.

[21]  Narendra Jussien,et al.  Solving dynamic timetabling problems as dynamic resource constrained project scheduling problems using new constraint programming tools , 2003 .

[22]  Gérard Ferrand,et al.  Correctness of Constraint Retraction Algorithms , 2003, FLAIRS.

[23]  Narendra Jussien,et al.  Solving Dynamic Resource Constraint Project Scheduling Problems Using New Constraint Programming Tools , 2002, PATAT.

[24]  Narendra Jussien,et al.  Constraint programming for dynamic scheduling problems , 2004 .