Enhanced multi-objective solution approach for multiple quality characteristics optimisation problems considering predictive uncertainties

Abstract

Purpose

The purpose of this paper is to address three key objectives. The first is the proposal of an enhanced multiobjective optimisation (MOO) solution approach for the mean and mean-variance optimisation of multiple “quality characteristics” (or “responses”), considering predictive uncertainties. The second objective is comparing the solution qualities of the proposed approach with those of existing approaches. The third objective is the proposal of a modified non-dominated sorting genetic algorithm-II (NSGA-II), which improves the solution quality for multiple response optimisation (MRO) problems.

Design/methodology/approach

The proposed solution approach integrates empirical response surface (RS) models, a simultaneous prediction interval-based MOO iterative search, and the multi-criteria decision-making (MCDM) technique to select the best implementable efficient solutions.

Findings

Implementation of the proposed approach in varied MRO problems demonstrates a significant improvement in the solution quality in worst-case scenarios. Moreover, the results indicate that the solution quality of the modified NSGA-II largely outperforms those of two existing MOO solution strategies.

Research limitations/implications

The enhanced MOO solution approach is limited to parametric RS prediction models and continuous search spaces.

Practical implications

The best-ranked solutions according to the proposed approach are derived considering the model predictive uncertainties and MCDM technique. These solutions (or process setting conditions) are expected to be more reliable for satisfying customer specification compared to point estimate-based MOO solutions in real-life implementation.

Originality/value

No evidence exists of earlier research that has demonstrated the suitability and superiority of an MOO solution approach for both mean and mean-variance MRO problems, considering RS uncertainties. Furthermore, this work illustrates the step-by-step implementation results of the proposed approach for the six selected MRO problems.

Citation

Sharma, A.K. and Mukherjee, I. (2020), "Enhanced multi-objective solution approach for multiple quality characteristics optimisation problems considering predictive uncertainties", International Journal of Quality & Reliability Management, Vol. 37 No. 1, pp. 112-144. https://doi.org/10.1108/IJQRM-01-2019-0011