Ayush Joshi
ABSTRACT
Artificial Immune algorithms are relatively new randomized meta-heuristics and not a lot of work has been done on parallel immune algorithms yet. Most of these implementations use some version of the first generation artificial immune algorithms. In this research a novel parallel artificial immune algorithm for optimization is proposed based on cutting edge research in the study of germinal center reaction. This parallelism of the algorithm is inherent in the system as a whole, which is different than other parallel implementations of nature inspired algorithms, where several instances of the algorithm is run multiple times to exploit parallel architecture of computers. This system is being developed with input from immunologist and incorporates new ideas which have not been explored before. Some preliminary results are presented which hint that it could perform better than the evolutionary algorithm ((1+1)EA), with which it is compared. The algorithm is not limited to optimization and in the future the research will look into other application areas. Also limitations, improvements and applications where it excels, will be explored in the research.
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Index Terms
- Design of a parallel immune algorithm based on the germinal center reaction
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