Ecological sports tourism based on multi population evolutionary algorithm and entrepreneurship environment for sustainable development

With the rapid development of the national economy and the continuous improvement of people's living standards, more and more people choose to travel to experience the physical and mental relaxation brought by a beautiful journey. However, due to China's large population and tight travel time, the enthusiasm for tourism has been greatly reduced. Therefore, China's tourism development needs to be further strengthened. Sports tourism is a new tourism product in China, and corresponding sports tourism is also a new discipline. At present, if China's sports tourism is to develop rapidly, it is urgent to study the planning and design of tourism routes. This paper optimized tourism routes through multi population evolutionary algorithms to improve tourists' tourism experience and meet the needs of tourists in terms of time and cost. By comparing the route optimization between the artificial fish swarm algorithm and the improved artificial fish swarm algorithm, the improved artificial fish swarm algorithm could achieve convergence on the local extreme value problem when the number of iterations was 120, which was earlier than the artificial fish swarm algorithm, and has better convergence accuracy and better stability. Therefore, the improved artificial fish swarm algorithm can better realize the path planning of sports tourism and the management of sustainable development of ecological sports tourism.