Traffic travel service selection based on hybrid optimization algorithm
Wanchun Yang, Chenxi Zhang · 2021
With the development of information technology in transportation industry, it becomes an important application of intelligent transportation system to provide real-time and effective travel services. The existing traffic travel service composition model is based on the assumption of single request, and it can not build composition according to granularity. Aiming at the problem of requests and granularity, from the two dimensions of transaction and quality of service (QoS), this paper presents an evaluation model of service composition which considers concurrent requests and multi-granularity. Based on the model, the paper proposed a method based on hybrid optimization algorithm. The proposed algorithm combined particle swarm optimization, crossover and mutation operators with priority, simulated annealing algorithm to get the optimal value. Experimental results show that our approach can guarantee QoS of service selection with low time cost.