A bio inspired estimation of distribution algorithm for global optimization

Abstract

This paper introduces a new bio-inspired Estimation of Distribution Algorithm for global optimization that integrates the quantum computing concepts with the immune clonal selection, vaccination process and Estimation of Distribution Algorithm (EDA). EDA is employed in the vaccination process to improve the solutions diversity and maintain high quality solutions in addition to its ability to avoid falling in local optimum for multi modal problems. The proposed algorithm is implemented and evaluated using standard benchmark test problems. Experimental results are compared with the quantum inspired immune clonal algorithm (QICA) and the QICA- with vaccine algorithm, where the proposed algorithm is superior to both of them. The obtained results carried out, it is performing well in terms of the solutions quality and diversity, and it is superior to both of compared algorithms. © 2012 Springer-Verlag.