Solving TSP Using Advanced Crossover & Mutating Operators of Genetic Algorithm

In this paper we develops a new crossover and mutating operator, Round crossover (RX) and Round mutating (RM) operator, for a genetic algorithm that generates high quality solutions to the Traveling Salesman Problem (TSP). The round crossover operator constructs an offspring from a pair of parents in a circular way using better edges on the basis of their values that may be present in the parents’ structure maintaining the sequence of nodes in the parent chromosomes. The round mutation applied to the resultant chromosome after crossover by selecting a random cut point and then joining the remaining substring to first substring in circular way. The efficiency of the RX is compared as against some existing crossover operators; namely, edge recombination crossover (ERX), Order crossover (OX) and partially Matched crossover (PMX) for some benchmark TSPLIB instances. Experimental results show that the new crossover operator is better than the PMX, ERX and OX.