Asynchronous parallel search by the parallel genetic algorithm

Author

Mühlenbein, Heinz

Author_Institution

GMD Schloss Birlinghoven, Sankt Augustin, Germany

fYear

1991

fDate

2-5 Dec 1991

Firstpage

526

Lastpage

533

Abstract

The parallel genetic algorithm (PGA) is a prototype of a new kind of a distributed algorithm. It is based on a parallel search by individuals all of which have the complete problem description. The information exchange between the individuals is done by simulating biological principles of evolution. The PGA is totally asynchronous, running with maximal efficiency on MIMD parallel computers. The search strategy of the PGA is based on a small number of intelligent and active individuals, whereas a GA uses a large population of passive individuals. The author shows the power of the PGA with two combinatorial problems-the graph partitioning problem and the autocorrelation problem. In these examples, the PGA has found solutions of very large problems, which are comparable or even better than any other solution found by other heuristics

Keywords

genetic algorithms; parallel algorithms; search problems; MIMD parallel computers; asynchronous parallel search; autocorrelation problem; biological principles; complete problem description; distributed algorithm; graph partitioning; parallel genetic algorithm; Autocorrelation; Biological system modeling; Biology computing; Computational modeling; Concurrent computing; Distributed algorithms; Electronics packaging; Evolution (biology); Genetic algorithms; Prototypes;

fLanguage

English

Publisher

ieee

Conference_Titel

Parallel and Distributed Processing, 1991. Proceedings of the Third IEEE Symposium on

Conference_Location

Dallas, TX

Print_ISBN

0-8186-2310-1

Type

conf

DOI

10.1109/SPDP.1991.218254

Filename

218254