Membrane Computing Inspired Genetic Algorithm on Multi-Core Processors
Ali Maroosi and Ravie Chandren Muniyandi
DOI : 10.3844/jcssp.2013.264.270
Journal of Computer Science
Volume 9, Issue 2
Membrane computing is a branch of natural computing. Several studies have recently attempted to utilize the structure of membrane computing to improve intelligent algorithms. These studies have applied communication rules in membrane models to facilitate information exchange between membranes, thereby improving the performance of those algorithms. However, parallel membrane computing has not yet been considered. This study proposes a membrane computing-inspired genetic algorithm. Similar to previous studies, the algorithm also uses communication rules to facilitate information exchange. In this study, an appropriate membrane computing-inspired genetic algorithm is defined, in which each membrane can be executed over different cores in a parallel manner. The proposed algorithm can be executed over different cores and uses multi-core processing to implement parallel membrane computation. Simulation with a Colville minimization problem shows that the membrane computing inspired genetic algorithm has improved performance, with a mean error of the solution 61.9 times better than genetic algorithm.
© 2013 Ali Maroosi and Ravie Chandren Muniyandi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.