Parallel genetic algorithm taxonomy

—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. In this paper 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) we have recently developed.

• Type: Conference
• Year: 1999
• Where: KES
• Authors: Mariusz Nowostawski, Riccardo Poli
• Keywords: Dynamic Deme Model, Information Management, KES 1999, Parallel Genetic Algorithms, Powerful Search Techniques