A study of a parallelized immune coevolutionary algorithm for division-of-labor problems

Recently, a number of parallelized optimization algorithms have been proposed. We have proposed a co-evolutionary immune algorithm (IA) to solve the division-of-labor problems, in particular the n-th agent’s travelling salesman problem (n-TSP). In this article, we extend the co-evolutionary IA for a large-scale n-TSP with (1) an improvement for the search speed through parallelized search on the PC-cluster, and (2) the introduction of a new division-processing “pre-estimated division processing” to improve the search ability. Some computational experiments show the proposed method can obtain better quality solutions for division-of-labor problems, and present an applicable parameter cofinguration.

Authors and Affiliations

1. Department of Information Engineering, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa, 903-0213, Japan

   Naruaki Toma, Satoshi Endo & Koji Yamada

Corresponding author

Correspondence to Naruaki Toma.

This work was presented, in part, at the 9th International Symposium on Artificial Life and Robotics, Oita, Japan, January 28–30, 2004