Article ID: | iaor20002948 |
Country: | United States |
Volume: | 1 |
Issue: | 3 |
Start Page Number: | 177 |
End Page Number: | 206 |
Publication Date: | Jul 1995 |
Journal: | Journal of Heuristics |
Authors: | Michalewicz Zbigniew |
Keywords: | evolutionary algorithms, genetic algorithms |
Evolutionary computation techniques, which are based on a powerful principle of evolution, survival of the fittest, constitute and interesting category of heuristic search. In other words, evolutionary techniques are stochastic algorithms whose search methods model some natural phenomena: genetic inheritance and Darwinian strife for survival. Any evolutionary algorithm applied to a particular problem must address the issue of genetic representation of solutions to the problem and genetic operators that would alter the genetic composition of offspring during the reproduction process. However, additional heuristics should be incorporated in the algorithm as well; some of these heuristic rules provide guidelines for evaluating (feasible and infeasible) individuals in the population. This paper surveys such heuristics and discusses their merits and drawbacks.