Prof. Dr.-Ing. Jürgen Sauer

 Associate Professor
   Carl von Ossietzky Universität Oldenburg
   Fakultät II, Department für Informatik
   D-26111 Oldenburg, Germany

   Tel:      ++49-(0)441-9722-122
   Office: Escherweg 2, O46  (OFFIS-Building) 



  • Visiting Research Fellow at Singapore Institute of Manufacturing Technology (2007-09)
  • Head of Computer Center of the CvO University of Oldenburg (2003-06)
  • more


Topics are business informatics (modeling, systems and IT-management), software engineering,
artificial intelligence and intelligent systems (esp. knowledge-based scheduling).
See more (in German)


    The research focuses on intelligent scheduling and intelligent IT service management.
    • Intelligent Scheduling
      covers modeling and solving scheduling problems mainly by using Artificial Intelligence approaches and has a long tradition since 1987. The research focuses on intelligent scheduling within supply chains
      (multi-site scheduling) including the modeling of different scheduling problems, the solving of
      scheduling problems using AI methods and the development of software systems including
      graphical user-interfaces for scheduling applications. Application areas are production,
      transport, projects, staff scheduling and others.
      The German research is centered in the
      special interest group on planning/ scheduling and configuration/ design within the GI.
      I am the speaker of this SIG.  Additional information in German.
  • Intelligent IT service management
    is around managing computer centers. Optimal/ intelligent management of IT services (e.g. large application systems or computer centers) also named adaptive computing is in the focus. Here topics like intelligent monitoring and control of virtual systems are investigated.

        See also publications  and student projects.

  • Project scheduling (ongoing): investigating strategies to be used in project and multi-project scheduling, especially in reactive scenarios
  • Visualization of scheduling strategies(ongoing): how to visualize the algorithms and strategies used in scheduling. The Visualization can be used in blended learning formats. Strategies are e.g. meta-heuristics, evolutionary algorithms, constraints, fuzzy logic, swarm intelligence.
  • Scheduling4Green (ongoing): Scheduling approaches are developed that help to reduce the power consumption e.g. in the chemical production. 
  • Vertical Data Integration for reactive scheduling (<2012): in reactive scheduling it is necessary to provide the events that affect the scheduling environment. It is investigated which are the important data and how these can be selected and used on several hierachical scheduling levels.
  • COSS (2006 - 2010): On the basis of the results from the MUST and AMPA project cooperating scheduling systems are investigated. This includes agent based cooperation in multi-site scheduling environments (e.g. supply chains) as well as specific scheduling approaches in specific scheduling domains within the supply chain.
  • PEP (2003 - 2008): The main goal of this project is the development and comparison of scheduling approaches for workforce scheduling mainly in retail and medical services.
  • AMPA (1998 - 2002): Within AMPA (Agent-based Multi-Site Planning and Scheduling Application Framework) an agent-based platform-independent system for scheduling tasks within a distributed supply chain architecture (including production, transport, storage) was developed.
  • SSWB (1994 - 2001): The Scheduling Systems Workbench (SSWB) intends to support the development of scheduling systems. It combines software engineering knowledge with specific knowledge about building scheduling systems to provide a toolbox for building scheduling systems.
  • MUST (1994 - 2002): The MUST (Multi-Site Scheduling System) project dealt with the problem of coordinating distributed scheduling systems to reach some global goals. The system combines global and local scheduling activities on several scheduling layers. Predictive as well as reactive scheduling is possible.
  • MARTIN (1993 -1998): In the MARTIN project an multi-agent system was developed that supports reactive scheduling.
  • GAP (1992 - 1996): GAP combines Genetic Algorithms and Constraint Programming to support the solution of combinatorial optimization problems. Scheduling is one of the possible application areas.
  • META-PLAN (1990 - 1992): In META-PLAN so called meta-knowledge about scheduling is used to describe (using a language called HERA: heuristics for representation of scheduling knowledge) and select scheduling strategies.
  • MEDICUS (1990 - 1993): MEDICUS is a scheduling system to be used in the heart surgery of a hospital. It supports scheduling of operation theaters and care sections.
  • PSY/ REAKTION (1989 - 1991): The system PSY supports the scheduling personal in discrete manufacturing processes of a fittings company. It focuses on predictive scheduling. The system REAKTION focuses on reactive scheduling and realizes a manual or automatic rescheduling due to typical disturbances in the production.
  • PROTOS (1988 - 1993): Within the EUREKA-Projekts PROTOS a knowledge-based system for scheduling process orientied production in the chemical industry was developed.

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