Skoči na glavni sadržaj

Izvorni znanstveni članak

The Spirit of Evolutionary Algorithms

Zbigniew Michalewicz ; Department of Computer Science, University of North Carolina, Charlotte, USA, and Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
Susana Esquivel ; Proyecto 338403, Departamento de Informatica, Facultad de Cs. Fisico-Matematicas y Naturales, Universidad Nacional de San Luis, 5700-San Luis, Argentina
Raul Gallard ; Proyecto 338403, Departamento de Informatica, Facultad de Cs. Fisico-Matematicas y Naturales, Universidad Nacional de San Luis, 5700-San Luis, Argentina
Maciej Michalewicz ; Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
Guo Tao ; State Key Laboratory of Software Engineering, Wuhan University, Wuhan, Hubei, P.R. China
Krzysztof Trojanowski ; Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland


Puni tekst: engleski pdf 9.925 Kb

str. 1-18

preuzimanja: 177

citiraj


Sažetak

Evolutionary algorithms (EAs), which are based on a powerful principle of evolution: survival of the fittest, and which model some natural phenomena: genetic inheritance and Darwinian strife for survival, constitute an interesting category of modern heuristic search. During the last two decades there has been a growing interest in these algorithms; today, many complex software systems include at least some evolutionary component.

However, the process of building an evolutionary program is still art rather than science; often it is based on the intuition and experience of the designer. In this introductory article we present some important ideas behind the construction of evolutionary algorithms. These ideas are illustrated by three test cases: the transportation problem, a particular nonlinear parameter optimization problem, and the traveling salesman problem. We conclude the paper with a brief discussion on how an evolutionary algorithm can be tuned to the problem while solving it, which may increase further efficiency of the algorithm in a significant way.

Ključne riječi

evolutionary algorithms

Hrčak ID:

150196

URI

https://hrcak.srce.hr/150196

Datum izdavanja:

30.3.1999.

Posjeta: 471 *