Theory Driven Design of Efficient Genetic Algorithms for a Classical Graph Problem

Chapter
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 62)

Abstract

This paper presents a principled way of designing a genetic algorithm which can guarantee a rigorously proven upper bound on its optimization time. The shortest path problem is selected to demonstrate how level-based analysis, a general purpose analytical tool, can be used as a design guide. We show that level-based analysis can also ease the experimental burden of finding appropriate parameter settings. Apart from providing an example of theory-driven algorithmic design, we also provide the first runtime analysis of a non-elitist population-based evolutionary algorithm for both the single-source and all-pairs shortest path problems.

Keywords

Runtime analysis Genetic algorithms Level-based analysis Shortest path problems 

Notes

Acknowledgements

This research received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement no 618091 (SAGE) and from the EPSRC under grant agreement no EP/M004252/1.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.The University of SheffieldSheffieldUK
  2. 2.School of Computer ScienceUniversity of BirminghamBirminghamUK

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