Abstract
In this paper, we propose an optimization algorithm inspired by the immune response mechanism and apply it to traveling salesman problem (TSP). We test the proposed algorithm by the simulations on randomly generated 100 data sets of 10-city problems and two of TSPLIB benchmark problems: ulysses22 (22-city) and eil51 (51-city). The simulation results illustrate that the proposed algorithm can find one hundred percent valid solutions in short computation time, and the solution quality is very good.
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