  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.
