Intelligent Tourism Route Optimization Method Based on the Improved Genetic Algorithm

This paper focuses on the problem of intelligent tourism route optimization, which is very important for tourism industry development. The main innovation of this paper is to convert the tourism route optimization problem to travelling salesman problem, and then presents an improved genetic algorithm to solve the travelling salesman problem. In order to enhance the performance of standard genetic algorithm, we combine the immune algorithm and genetic algorithm together. In particular, immune genetic algorithm means a global search which integrating immune system and genetic algorithm together. In order to verify the performance of the proposed algorithm, we define path representation to optimize tourism route, and then apply a weight matrix to describe distance between different tourist spots. Experimental results demonstrate the effectiveness of our algorithm.