Artificial immune systems are a kind of new computational intelligence methods which draw inspiration from the human immune system. Most immune system inspired optimization algorithms are based on the applications of clonal selection and hypermutation, and known as clonal selection algorithms. These clonal selection algorithms simulate the immune response process based on principles of Darwinia...

The clonal selection principle explains the basic features of an adaptive immune response to a antigenic stimulus. It established the idea that only those cells that recognize the antigens are selected to proliferate and differentiate. This paper explains a computational implementation of the clonal selection principle that explicitly takes into account the affinity maturation of the immune res...

In this paper, we propose a probabilistic modeling clonal selection algorithm which combines the clonal selection algorithm (CSA) and the probabilistic modeling (PM) for traveling salesman problem (TSP). The clonal selection algorithm is employed by the natural immune system to define the basic features of an immune response to an antigenic stimulus, can initialize antibodies and maintain the p...

The university timetabling, examination and course, are known to be highly constrained optimization problems. Metaheuristic approaches, and their hybrids, have successfully been applied to solve the problems. This paper presents three artificial immune algorithms, the algorithms inspired by the immune system, for university timetabling; clonal selection, immune network and negative selection. T...

Antigen receptor diversity underpins adaptive immunity by providing the ground for clonal selection of lymphocytes with the appropriate antigen reactivity. Current models attribute T cell clonal selection during the immune response to T-cell receptor (TCR) affinity for either foreign or self peptides. Here, we report that clonal selection of CD4(+) T cells is also extrinsically regulated by B c...

Positive and negative selection of thymocytes in the thymus are critical for the development of a mature and self-tolerant T-cell repertoire. The proapoptotic Bcl-2 family member Bim is important for negative selection by inducing apoptosis in thymocytes receiving a strong signal through their antigen receptor. However, in the case of ubiquitous self-antigens (UbA), Bim is not required for the ...

Two metaheuristic algorithms namely Artificial Immune Systems (AIS) and Genetic Algorithms are classified as computational systems inspired by theoretical immunology and genetics mechanisms. In this work we examine the comparative performances of two algorithms. A special selection algorithm, Clonal Selection Algorithm (CLONALG), which is a subset of Artificial Immune Systems, and Genetic Algor...