Development of a soft computing-based framework for engineering design optimisation with quantitative and qualitative search spaces

Most real world engineering design optimisation approaches reported in the literature aim to find the best set of solutions using computationally expensive quantitative (QT) models without considering the related qualitative (QL) effect of the design problem simultaneously. Although, the QT models provide various detailed information about the design problem, unfortunately, these approaches can result in unrealistic design solutions. This paper presents a soft computing-based integrated design optimisation framework of QT and QL search spaces using meta-models (design of experiment, DoE). The proposed approach is applied to multi-objective rod rolling problem with promising results. The paper concludes with a detailed discussion on the relevant issues of integrated QT and QL design strategy for design optimisation problems outlining its strengths and challenges.