Research On Collaborative Optimization Model Of Tourism Resources And Road Network

With the rapid social economic development in recent years,the development mode of the tourism industry has gradually transformed into the mode of Regional cooperation system integration from the mode of noncooperation and advanced development. As basic and leading power of tourism industry, transportation is the key factors for the scale and sustainable development of regional tourist industry. By reasonably optimizeing collocation of regional tourism resource and seeking the best combination points of tourism and transportation development, it can effectively enhance the core competitiveness of regional tourism meanwhile promoting the construction of transport infrastructure and service level of transportation. Therefore, the collaborative optimization research of tourism resources and road network has become extremely important in the early stages of the planning.First of all, this paper introduces the theory and analysis of social networks to build regional tourism transport network structure model from two aspects of tourist flow network and transportation network by using the topological characteristics of the network, in order to discuss the spatial layout model and the network structural characteristics of regional tourism transport network. By analysising of the roles and functions of network, it can explain the law of time-space evolution and diffusion as well as internal mechanism of the regional tourist flow. The tourist travel’s dependence on the transport network had been verified by comparative analysis. Also, it can verify the potential point of tourism resource development and highway network optimization for providing reliable alternatives of the collaborative optimization of tourism resources and road network.On the basis of clearing the game relations between decision makers of planning and travelers, we consider a collaborative optimization of tourism resources and road network and analysis the impacts of optimization on the traffic volume distribution. It can build bi-level programming model by determining the upper objective as maximizing the social net income, which can be divided into four parts of the least construction cost of highway and tourism, savings of highway network optimization and tourism revenues. Meanwhile, the lower objective is the optimal travelers’ efficiency. According to the characteristics of the model, solving steps are given by using genetic algorithm. The model optimizes tourism facility locations while formed a complete set of road infrastructure, in order to avoid the unreasonable allocation of system resources effectively and improve the efficiency of the synergy between systems. Finally, the case of Heilongjiang province is used to verify the rationality of the collaborative optimization model. Meanwhile, we conduct a sensitivity analysis to investigate the impacts of several key parameters on the optimal solution. It provides a theoretical basis for the integrated development of tourism resources and highway network in the future.