A Taxonomy of Evolutionary Algorithms in Combinatorial Optimization

  • Authors:
  • Patrice Calégari;Giovanni Coray;Alain Hertz;Daniel Kobler;Pierre Kuonen

  • Affiliations:
  • Swiss Federal Institute of Technology, Department of Mathematics and Computer Science, CH-1015 Lausanne, Switzerland. Patrice.Calegari@epfl.ch;Swiss Federal Institute of Technology, Department of Mathematics and Computer Science, CH-1015 Lausanne, Switzerland. Giovanni.Coray@epfl.ch;Swiss Federal Institute of Technology, Department of Mathematics and Computer Science, CH-1015 Lausanne, Switzerland. Alain.Hertz@epfl.ch;Swiss Federal Institute of Technology, Department of Mathematics and Computer Science, CH-1015 Lausanne, Switzerland. Daniel.Kobler@epfl.ch;Swiss Federal Institute of Technology, Department of Mathematics and Computer Science, CH-1015 Lausanne, Switzerland. Pierre.Kuonen@epfl.ch

  • Venue:
  • Journal of Heuristics
  • Year:
  • 1999

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper shows how evolutionary algorithms can be described in aconcise, yet comprehensive and accurate way. A classification scheme isintroduced and presented in a tabular form called TEA (Table of EvolutionaryAlgorithms). It distinguishes between different classes of evolutionaryalgorithms (e.g., genetic algorithms, ant systems) by enumerating the fundamental ingredients of each of these algorithms. At the end, possible uses of the TEA are illustrated on classical evolutionary algorithms.