Title :
Parallel genetic algorithm taxonomy
Author :
Nowostawski, Mariusz ; Poli, Riccardo
Author_Institution :
Dept. of Inf. Sci., Otago Univ., Dunedin, New Zealand
Abstract :
Genetic algorithms (GAs) are powerful search techniques that are used to solve difficult problems in many disciplines. Unfortunately, they can be very demanding in terms of computation load and memory. Parallel genetic algorithms (PGAs) are parallel implementations of GAs which can provide considerable gains in terms of performance and scalability. PGAs can easily be implemented on networks of heterogeneous computers or on parallel mainframes. We review the state of the art on PGAs and propose a new taxonomy also including a new form of PGA (the dynamic deme model) which was recently developed
Keywords :
genetic algorithms; parallel algorithms; parallel machines; search problems; PGAs; computation load; dynamic deme model; networks of heterogeneous computers; parallel genetic algorithm taxonomy; parallel implementations; parallel mainframes; search techniques; Computer science; Concurrent computing; Electronics packaging; Genetic algorithms; Genetic mutations; Information science; Performance gain; Phase change materials; Scalability; Taxonomy;
Conference_Titel :
Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-5578-4
DOI :
10.1109/KES.1999.820127
