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This paper addresses the question of how to make available and how to get realistic insight into the behavior of hard algorithms for application fields such as scheduling. The first author acknowledges support from the Deutsche Forschungsgemeinschaft under grant Mo446 1–3 and Sonderforschungsbereich 373. JavaScript is currently disabled, this site works much better if you enable JavaScript in your browser. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. A typical situation in this context is the availability of hundreds of algorithms for special subclasses of certain problems where one of the main difficulties is to handle these algorithms simultaneously and make available knowledge about when and how to apply a particular algorithm, using statistical information on the suitability of certain algorithms under appropriate conditions.
Major questions concern “accounting problems” when particular algorithmic tasks are required to apply special methods but might also be useful for other methods. In particular, the question of finding adequate software-engineering strategies and software-development environments for such work is addressed.


Also, the paper reviews recent developments at the Research Institute for Applied Knowledge Processing (FAW) in Ulm and describes a method base for scheduling algorithms built within the framework of a cooperative effort between FAW and the Technical University of Berlin.
Radermacher, Design aspects of an advanced DSS for scheduling problems in civil engineering, Dec. Geoffrion, The SML language for structured modeling, WMSI Working Paper 378, Anderson Graduate School of Management, UCLA (1990).[9]A. Entwicklung und Implementierung eines Systems fur den problemorientierten Zugriff auf rechnergestutzte Losungsverfahren, Diplomarbeit FAW-B-92003 (1992).[12]M. Vicuna, MIDA: an open systems architecture for model-oriented integration of data and algorithms, Dec.
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Solte,Open Systems Ein lernendes Verwaltungssystem fur die rechnerunterstutzte Methodenkonstruktion im Bereich des Operations Research.



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