E-mail : fabdennad,[email protected] Abstract : Timetabling the courses offered at the Computer Science Department of the University of Munich requires the processing of hard and soft constraints. Hard constraints are conditions that must be satisfied, soft constraints however may be violated, but should be satisfied as much as possible. This paper shows how to model our timetab...

We use Constraint Logic Programming and develop methods , techniques and concepts for a combined automatic and interactive timetabling of university courses and school curricula. An instance of such a timetabling system was developed for the Charit e Medical Faculty at the Humboldt University, Berlin. This paper looks at methods and techniques for solving this timetabling problem. An essential ...

The International Timetabling Competition 2019 (ITC 2019) posed a university timetabling problem involving assigning classes to times and rooms for an entire semester while students required classes. We propose new mixed integer programming (MIP) formulation of the problem. MIP takes advantage different graph structures in conflict graphs construct strong constraints. In addition, we introduce ...

This paper presents an innovative approach to curriculum-based timetabling. Curricula are defined by a rich model that includes optional courses and course groups among which students are expected to take a subset of courses. Transformation of the curriculum model into the enrollment model is proposed and a local search algorithm generating corresponding enrollments is introduced. This enables ...

In manufacturing systems, generally employee timetabling and job shop scheduling is considered to be too hard and complex. To achieve an integrated manufacturing environment, the integration of employee timetabling and job shop scheduling is essential. It is a process of assigning employees into work slots in a pattern according to the hierarchy level of the employee, job allotment, individual ...

The university course timetabling problem is a typical combinatorial optimization problem. This paper tackles the multi-objective university course timetabling problem (MOUCTP) and proposes a guided search non-dominated sorting genetic algorithm to solve the MOUCTP. The proposed algorithm integrates a guided search technique, which uses a memory to store useful information extracted from previo...

Scheduling exams in colleges are a complicated job that is difficult to solve conventionally. Exam timetabling one of the combinatorial optimization problems where there no exact algorithm can answer problem with optimum solution and minimum time possible. This study investigated University Toronto benchmark dataset, which provides 13 real instances regarding scheduling course from various inst...