To address the traditional Traveling Salesman Problems (TSP) with the combinatorial explosion property, a novel MHC-inspired antibody clone optimization algorithm (COAMHC) was proposed by drawing inspiration from the features of Major Histocompatibility Complex (MHC) in the biological immune system. COAMHC preserves elitist antibody genes through the MHC string to improve its local search capability and improves the diversity of antibody population by gene mutation and some new random immigrant antibodies to enhance its global search capability. The experiments of comparing COAMHC with the canonical clone selection algorithm (CLONALG) were carried out for the TSP and results indicated that the performance of COAMHC is better than that of CLONALG. The COAMHC algorithm provides new opportunities for solving previously intractable optimization problems such as TSP.
