ABSTRACT

In this work Traveling salesperson problem is taken as Domain. TSP has long been known to be NP-complete and is a standard example of such problems. Genetic Algorithm (GA) is an approximate algorithm that doesn’t always aim to find the shortest tour but to find a reasonably short tour quickly, which is a search procedure inspired by the mechanisms of biological evolution. In genetic algorithms, crossovers are used as a main search operator for TSP. Briefly speaking: the role of crossovers is to generate offspring that are better tours by preserving partial tours from the parents. There were a lot attempts to discover an appropriate crossover operator. This paper presents the strategy which used to find the nearly optimized solution to these type of problems. It is the order crossover operator (OX) which was proposed by Davis, which constructs an offspring by choosing a subsequence of one parent and preserving the relative order of cities of the other parent.