Algorithmic Complexity Research on Foreign-related Tourism English Education and Talent Cultivation Models in the Context of Free Trade Port

Abstract

Abstract In today’s booming development of free trade ports, China, as a big country of inbound and outbound tourism, has put forward higher requirements for the talent cultivation mode of foreign-related tourism English. This paper takes the characteristics of foreign-related tourism English as the entry point and establishes the practical teaching system and the four-in-one talent cultivation mode of foreign-related tourism English. The multi-objective optimization model for cultivating foreign tourism English talents is proposed, with the objective function of enhancing the quality of foreign tourism English talents, and the corresponding constraints are set. The multi-objective optimization model is solved using the DQN model, and a strategy gradient algorithm-based model training optimization strategy is proposed. The test conditions of foreign-related tourism English talent cultivation are set, simulation experiments are carried out, and teaching experiments are compared based on the optimal scheme. The training loss obtained by the DQN model after 1700 iterations fluctuates between [0.015,0.019], and when the training period is set to 2 years, the cumulative return of foreign-related tourism English talent cultivation can reach 623.87%, and the maximum retracement is only - 5.457%. The optimal talent cultivation program’s average score is 14.1 points higher than the ordinary version. Foreign-related tourism English needs to be fully integrated with the actual demand for talent, and the faculty and policy guidelines help to enhance the quality of foreign-related tourism English talent training.