Abstract—The Clonal selection is a mechanism used by the natural immune system to select cells that recognize the antigens to proliferate. The proliferated cells are subject to an affinity maturation process, which improves their affinity to the selective antigens. The concept of Clonal selection is an important one to the success of the human immune system, andit provides an excellent example of the principles of selection at work. The positive and negative selection is another interesting mechanism in the immune system that works together to both retain cells that recognize the self peptides, while also removing cells that do not recognize any self peptides. In this paper, a cloning-based algorithm inspired by the Clonal and the positive/negative selection mechanism of the natural immune system is presented. The well known TSP is used to illustrate the approach. Simulations demonstrate that this approach generates good solutions to traveling salesman problem.
Index Terms—Artificial Immune System, Clonal Selection, Hamiltionian circuit, Negative/Positive selection, Traveling salesman problem.
Tejbanta Singh Chingtham is with the Sikkim Manipal Institute of Technology, Majitar, Rangpo, East Sikkim – 737132, INDIA as a Reader in the Department of Computer Science and Engineering. (e-mail: cts@smuhmts.edu; phone +919734916135).
G. Sahoo is with Birla Institute of Technology, Mesra, Ranchi, Jharkhand as a Professor in Department of Information Technology. (e-mail: gsahoo@bitmesra.ac.in)
M. K. Ghose is with Sikkim Manipal Institute of Technology, Majitar, Rangpo, E-Sikkim, as a Professor in Department of Computer Science and Engineering (mkghose@smuhmts.edu)
Cite: Tejbanta Singh Chingtham, "Optimization of Path Finding Algorithm Using Clonal Selection: Application to Traveling Salesperson Problem," International Journal of Computer Theory and Engineering vol. 2, no. 2, pp. 290-294, 2010.
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