Genetic algorithms: a survey

Author

Srinivas, M. ; Patnaik, Lalit M.

Author_Institution

Motorola India Electron. Ltd., Bangalore, India

Volume

27

Issue

6

fYear

1994

fDate

6/1/1994 12:00:00 AM

Firstpage

17

Lastpage

26

Abstract

Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex landscapes. We introduce the art and science of genetic algorithms and survey current issues in GA theory and practice. We do not present a detailed study, instead, we offer a quick guide into the labyrinth of GA research. First, we draw the analogy between genetic algorithms and the search processes in nature. Then we describe the genetic algorithm that Holland introduced in 1975 and the workings of GAs. After a survey of techniques proposed as improvements to Holland´s GA and of some radically different approaches, we survey the advances in GA theory related to modeling, dynamics, and deception.<>

Keywords

genetic algorithms; reviews; search problems; deception; directed random searches; dynamics; genetic algorithms; modeling; optimization techniques; search processes; Genetic algorithms; Genetic mutations; Heuristic algorithms; Machine learning; Robustness; Search methods; Simulated annealing; Strategic planning; Technology planning; Very large scale integration;

fLanguage

English

Journal_Title

Computer

Publisher

ieee

ISSN

0018-9162

Type

jour

DOI

10.1109/2.294849

Filename

294849