关键词: 交互式蚁群优化, 蚁群优化, 人机交互, 汽车造型

Abstract: Interactive ant colony optimization (iACO) is a technique that optimizes target systems based on human evaluation. It can be used to solve the systems whose optimization indices are unable or difficult to be quantificated. Firstly, this paper analyzes the difficulties faced by iACO model. Nextly, aiming at the low performance of interactive ant system that is put forward by Tanabe et al., this paper proposes an improved iACO algorithm. The pheromone in the proposed model is updated with the best ant and limited to a certain range. The method of constructing solutions and evaluating strategies from the perspective of human-computer interaction are discussed. Finally, the  results of the experiments of function optimization and car styling draft design show that the proposed algorithm has higher optimization performance.

Key words: interactive ant colony optimization, ant colony optimization, human-computer interaction, car styling