CLONALG

At initial, initialization of a population of antibodies is presented. The antibodies present in a population set are evaluated based upon the described fitness function. On the virtue of their antigenic affinity the antibodies are chosen to proliferate and generate clones proportional to their affinity. Different CLONALG employ deterministic selection rule to choose better antibodies for proliferation. The problem concerning the deterministic rule is that merely best individuals are chosen, which results in a homogenous population or in other words in a premature convergence of the algorithm. To conquer such difficulty, for the proliferation of the high affinity antibodies, Roulette wheel selection rule is adopted. In this means, the diversity is kept in the clonal pool and a way to reach the optimal or near-optimal solution as much easier. As per to this rule, the antibodies are ranked as per to their fitness value. Explain f_i to express the rank the i^th individual of the population, the selection probability of all antibody k, is computed by:

The current algorithm is again based upon the clonal selection principle that implies that the highest affinity antibodies are chosen and proliferated via cloning procedure. Consequent clonal selection principle antibodies are proliferated that is cloned independently and proportionally to their antigenic affinity. The chosen or selected antibodies (s) are sorted in order and the number of clones to be produced is given by:

Here numerical control is the total number of clones to be produced for selected antibodies, numerical control (i) is the number of clones for i^th antibody; φ is the user explained multiplying factor.

In CLONALG, the variation in antibodies is performed via hyper-mutation and receptor editing mechanism. The hyper-mutation operator works in a same fashion as the mutation operator of Genetic algorithms. Conversely, the basic difference lies in such, the inferior antibodies are hyper-mutated at a higher rate as compare to the antibodies along with high antigenic affinity. Point mutation only generates new antibodies via altering one or more genes for example: flipping of binary bit, or, swapping of bits in permutation string based upon their hyper-mutation rate given by described equation:

                                                                 σ= exp (- δ f )....................Eqn(12)

Here, σ = rate of hyper-mutation;

δ = control factor of decay;

f = antigenic affinity. This is clear from the above equation that antibodies along with low affinity are mutated at higher rate than antibodies along with higher affinity. The mutation strategy should offer larger step size for lower affinity antibodies, and slight or minute step size for higher affinity.