Single-Mode Genetic Algorithms

  • Sönke Hartmann
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 478)


In this chapter, we discuss genetic algorithm (GA) heuristics for the RCPSP. The GAs make use of many of the concepts that were discussed in the previous chapter, such as schedule generation schemes, problem representations, and priority rule methods. We will also introduce some new approaches such as new operators, generalized representations, and a local search extension. In particular, we will introduce a representation which allows the GA to adapt itself by learning which algorithmic component should be used.


Genetic Algorithm Local Search Crossover Operator Priority Rule Activity List 
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-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Sönke Hartmann
    • 1
  1. 1.Institut für BetriebswirtschaftslehreUniversity of KielKielGermany

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