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Multi-objective robust optimization using a sensitivity region concept
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DOI：10.1007/s00158-004-0450-8.png)
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Abstract
En 中文
In multi-objective design optimization, it is quite desirable to obtain solutions that are multi-objectively optimum and insensitive to uncontrollable (noisy) parameter variations. We call such solutions robust Pareto solutions. In this paper we present a method to measure the multi-objective sensitivity of a design alternative, and an approach to use such a measure to obtain multi-objectively robust Pareto optimum solutions. Our sensitivity measure does not require a presumed probability distribution of uncontrollable parameters and does not utilize gradient information; therefore, it is applicable to multi-objective optimization problems that have non-differentiable and/or discontinuous objective functions, and also to problems with large parameter variations. As a demonstration, we apply our robust optimization method to an engineering example, the design of a vibrating platform. We show that the solutions obtained for this example are indeed robust.
Keywords:
multiple objectives
robust optimization
sensitivity analysis
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