Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Hartmann, S. (1999). Single-Mode Genetic Algorithms. In: Project Scheduling under Limited Resources. Lecture Notes in Economics and Mathematical Systems, vol 478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-58627-9_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-58627-9_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66392-8
Online ISBN: 978-3-642-58627-9
eBook Packages: Springer Book Archive