2001/06/02 by Hana Rudova, Hana Rudová, Rudova, Hana
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Constraint Satisfaction and Optimization #F.4.1 #FOS: Computer and information sciences #I.2.8 #I.6.5 #Programming Languages (cs.PL) #Scheduling and Timetabling Solutions #cs.AI #cs.PL
paper · pdf · doi:10.48550/arxiv.cs/0106004
10 pages; accepted to the Sixth Annual Workshop of the ERCIM Working Group on Constraints
arxiv created 2001/06/02 · openalex publication_date 2001/06/02 · arxiv updated 2009/11/30 · openalex created_date 2024/04/11 · openalex updated_date 2026/07/28
Classical notions of disjunctive and cumulative scheduling are studied from the point of view of soft constraint satisfaction. Soft disjunctive scheduling is introduced as an instance of soft CSP and preferences included in this problem are applied to generate a lower bound based on existing discrete capacity resource. Timetabling problems at Purdue University and Faculty of Informatics at Masaryk University considering individual course requirements of students demonstrate practical problems which are solved via proposed methods. Implementation of general preference constraint solver is discussed and first computational results for timetabling problem are presented.