Reducing the user fatigue in interactive design: Utilizing interactive genetic algorithm and the desired designs of former users

Abstract

Interactive evolutionary algorithms are a class of evolutionary algorithms adopted for customer centric product design. During the run of such algorithms, the customer (user) acts as a fitness function to evaluate the candidate designs based on his/her interests and preferences. These algorithms are usually iterated frequently to find the desirable design of customer; hence, the user fatigue problem during interaction with these algorithms is a major challenge. The present study develops a method to tackle this problem. In this method, the desired designs of former users are considered as valuable knowledge to support the algorithm execution in the future. This knowledge is applied to enrich the populations of interactive genetic algorithm to speed up finding the desired designs of users. The proposed method has been used for customer centric design of book covers. The results show that the proposed method improves the speed of algorithm and increase the user satisfaction. © 2020 [International Journal of Artificial Intelligence].