The GENIE is out! (Who needs fitness to evolve?)

Author

Chen, Stephen ; Smith, Stephen F. ; Guerra-Salcedo, César

Author_Institution

Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA

Volume

3

fYear

1999

fDate

1999

Abstract

“Survival of the fittest” is often seen as the driving force behind adaptation and evolution. For sure, all evolutionary algorithms use fitness based selection. However, it is not necessary to know where you are, to know where you are going. Similarly, it is not necessary to know the fitness of a solution, to find a better solution. The GENIE algorithm uses random parent selection and a non-elitist generational replacement scheme. Experiments on a non-trivial instance of the Traveling Salesman Problem show that heuristic operators in GENIE can converge to the optimal solution without evaluating fitness

Keywords

evolutionary computation; heuristic programming; random processes; travelling salesman problems; GENIE algorithm; Traveling Salesman Problem; adaptation; evolution; evolutionary algorithms; fitness based selection; heuristic operators; non-elitist generational replacement scheme; non-trivial instance; optimal solution; random parent selection; survival of the fittest; Assembly; Computer science; Evolutionary computation; Genetic algorithms; Robots; Traveling salesman problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on

Conference_Location

Washington, DC

Print_ISBN

0-7803-5536-9

Type

conf

DOI

10.1109/CEC.1999.785534

Filename

785534