In this paper, we investigate the relevance of two simple computational models of immunization in Time Dependent optimization (TDO) problems. At rst, we propose a Simple Arti cial Immune System (Sais) and experimentally compare its reactiveness and robustness to well known evolutionist approaches. Sais is then applied to a cyclic dynamical environment in order to evaluate its ability to feature an improved robustness when facing previously encountered optima. After discussing the limits of this approach, we propose a second algorithm (Yasais) designed to improve this so-called immunization process by stabilizing the way optima are memorized. Eventually, we discuss the results of both algorithms and underline how the latter features a quasi-optimal behavior.
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.