Hybrid ITO Algorithm for Large-Scale Colored Traveling Salesman Problem

In the fields of intelligent transportation and multi-task cooperation, many practical problems can be modeled by colored traveling salesman problem (CTSP). When solving large-scale CTSP with a scale of more than 1000 dimensions, their convergence speed and the quality of their solutions are limited. This paper proposes a new hybrid ITO (HITO) algorithm, which integrates two new strategies, crossover operator and mutation strategy, into the standard ITO. In the iteration process of HITO, the feasible solution of CTSP is represented by the double chromosome coding, and the random drift and wave operators are used to explore and develop new unknown regions. In this process, the drift operator is executed by the improved crossover operator, and the wave operator is performed by the optimized mutation strategy. Experiments show that HITO is superior to the known comparison algorithms in terms of the quality solution.