Omni-ainet: An Immune-inspired Approach For Omni Optimization

This work presents omni-aiNet, an immune-inspired algorithm developed to solve single and multi-objective optimization problems, either with single and multi-global solutions. The search engine is capable of automatically adapting the exploration of the search space according to the intrinsic demand of the optimization problem. This proposal unites the concepts of omni-optimization, already proposed in the literature, with distinctive procedures associated with immune-inspired concepts. Due to the immune inspiration, the omni-aiNet presents a population capable of adjusting its size during the execution of the algorithm, according to a predefined suppression threshold, and a new grid mechanism to control the spread of solutions in the objective space. The omni-aiNet was applied to several optimization problems and the obtained results are presented and analyzed. © Springer-Verlag Berlin Heidelberg 2006.4163 LNCS294308Bazaraa, M.S., Sherali, H.D., Shetty, C.M., (1993) Nonlinear Programming: Theory and Algorithms, , John-Wiley & Sons, 2nd. edBurnet, F.M., Clonal selection and after (1978) Theoretical Immunology, pp. 63-85. , Bell, G. I., Perelson, A. S., Pimgley Jr, G. H. (Eds.), Marcel Dekker IncCoello Coello, C.A., Cortés, N.C., Solving multiobjective optimization problems using an artificial immune system (2005) Genetic Programming and Evolvable Machines, 6, pp. 163-190De Castro, L.N., Timmis, J., (2002) An Introduction to Artificial Immune Systems: A New Computational Intelligence Paradigm, , Springer-VerlagDe Castro, L.N., Timmis, J., An artificial immune network for multimodal funcion optimization (2002) Proc. IEEE CEC, pp. 669-674. , USADe Castro, L.N., Von Zuberi, F.J., aiNet: An artificial immune network for data analysis (2001) Data Mining: A Heuristic Approach, pp. 231-259. , Abbass, H. A., Sarker, R. A., Newton, C. S. (Eds.), Idea Group Publishing, USA, Chapter XIIDe França, F.O., Von Zuben, F.J., De Castro, L.N., An artificial immune network for multimodal funcion optimization on dynamic environments (2005) Proc. GECCO, pp. 289-296. , Washington, DC, USADeb, K., Tiwari, S., Omni-optimizer: A procedure for single and multi-objective optimization (2005) LNCS, 3410, pp. 47-61. , Coello Coello, C. A., Aguirre, A. H., Zitzler, E. (Eds.) Proc. 3rd. EMO, MexicoGomes, L.C.T., De Sousa, J.S., Bezerra, G.B., De Castro, L.N., Von Zuben, F.J., Copt-aiNet and the gene ordering problem (2003) Information Technology Magazine, 3 (2), pp. 27-33. , Catholic University of BrasiliaHolland, P.W.H., Garcia-Fernandez, J., Williams, N.A., Sidow, A., Gene duplications and origins of the vertebrate development (1994) Dev. Supp., pp. 125-133Jerne, N.K., Towards a network theory of the immune system (1974) Ann. Immunol., Inst. Pasteur, 125 C, pp. 373-389Ohno, S., (1970) Evolution by Gene Duplication, , Allen and Unwin, London, UKZitzler, E., Thiele, L., Deb, K., Comparison of multiobjective evolutionary algorithms: Empirical results (2000) Evol. Computation, 8 (2), pp. 173-19