Genetic algorithms offer very good performances for solving large optimization problems, especially in the domain of error-correcting codes. However, they have a major drawback related to the time complexity and memory occupation when running on a uniprocessor computer. This paper proposes a parallel decoder for linear block codes, using parallel genetic algorithms (PGA). The good performance a...

Genetic algorithms (GAs) is a kind of powerful method for solving complex problems. Generally, parallel computing is used together with GAs to achieve better execution time and there exist several models for Parallel Genetic Algorithms (PGAs), such as master-salve model and island model. Currently, PC cluster is the common architecture for parallel computing with high performance-price-ratio. I...

This paper critically reviews the reported research on parallel single and multi-objective genetic algorithms. Many early efforts on single and multi-objective genetic algorithms were introduced to reduce the processing time needed to reach an acceptable solution. However, some parallel single and multi-objective genetic algorithms converged to better solutions as compared to comparable sequent...