Utilizing the uncertainty-based MADM-optimization approach to find robust-reliable design parameters for a platform-based product by considering aleatory uncertainties and human judgment effect

In this paper, a new methodology was proposed for finding optimal robust-reliable parameter values of a space-based earth observation (SEO) mission based on a predefined multi-purpose platform considering influential uncertainties and human judgment. A deterministic optimization was performed using an evolutionary algorithm on the basis of platform capability and mission-required performance, simulated by a dynamic simulation-based model. A set of non-dominated solutions with different behaviors emerged. Then, samples of these solutions were selected and an uncertainty analysis was carried out. After that, a multiple attribute decision-making (MADM) problem was formed with two groups of attributes related to constraints violations and variation of objective function value having unknown weights. Dominant ranking of the non-dominated solutions was obtained by simulating this MADM problem for adequate times with different random weights (human judgment effects). In the next step, given the outputs obtained from solving MADM problem, an optimal robust-reliable solution could be determined utilizing two approaches, response surface methodology (RSM) and forming a new uncertainty-based multidisciplinary design optimization (UMDO) problem. The results showed that utilizing MADM approach not only brings the effects of human judgment into design problem but also accelerates convergence to optimal robust-reliable solution in multimodal problems by bounding the search space without any risk regarding getting stuck in local optimal regions.

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