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

Authors:
Victor Oduguwa;Rajkumar Roy;Didier Farrugia
Affiliations:
Department of Enterprise Integration, School of Industrial and Manufacturing Science, Cranfield University, Building 53, Cranfield, Bedford MK43 0AL, UK;Department of Enterprise Integration, School of Industrial and Manufacturing Science, Cranfield University, Building 53, Cranfield, Bedford MK43 0AL, UK;Corus R, D and T, Swinden Technology Center, Rotherham S60 3AR, UK
Venue:
Applied Soft Computing
Year:
2007

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Abstract

Most real world engineering design optimisation approaches reported in the literature aim to find the best set of solutions using computationally expensive quantitative (Q^T) models without considering the related qualitative (Q^L) effect of the design problem simultaneously. Although, the Q^T 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 Q^T and Q^L 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 Q^T and Q^L design strategy for design optimisation problems outlining its strengths and challenges.