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Benchmark Instances for Project Scheduling Problems

  • Rainer Kolisch
  • Christoph Schwindt
  • Arno Sprecher
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 14)

Abstract

With the development of project scheduling models and methods arose the need for data instances in order to benchmark the solution procedures. Generally, benchmark instances can be distinguished by their origin into real world problems and artificial problems. The analysis of algorithmic performance on real world problem instances is of a high practical relevance, but at the same time it is only an analysis of individual cases. Consequently, general conclusions about the algorithms cannot be drawn. A solution procedure which shows very good performance on one real world instance might produce poor results on another. In order to allow a systematic evaluation of the performance of algorithms, characteristics of the projects have to be identified. The characteristics can then serve as the parameters for the systematic generation of artificial instances. The variation of the levels of these problem parameters in a full factorial design study allows to produce a set of well-balanced instances (cf. Montgomery 1976).

Keywords

Precedence Constraint Project Schedule Nonrenewable Resource Benchmark Instance Project Schedule Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Rainer Kolisch
    • 1
  • Christoph Schwindt
    • 1
  • Arno Sprecher
    • 1
  1. 1.Christian-Albrechts-Universität zu KielUniversität KarlsruheGermany

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