Vaccine Enhanced Artificial Immune System for Multimodal Function Optimization

This paper proposes the use of vaccine to promote exploration in the search space for solving multimodal function optimization problems using artificial immune system. In this method, first we divide the decision space into equal subspaces. Vaccine is then extracted randomly from each subspace. A few of these antigens are then injected into the algorithm to enhance the exploration of global and local optima. The vaccine is introduced in the form of suppressed antibodies. The goal of this process is to allocate the available antibodies at unexplored areas. Using this biologically motivated notion we design the vaccine enhanced artificial immune system for multimodal function optimization.