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Multi-objective robust optimization using a sensitivity region concept

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Abstract

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.

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of Maryland, College Park, Maryland, 20742, USA

    S. Gunawan & S. Azarm

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  1. S. Gunawan
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  2. S. Azarm
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Correspondence to S. Azarm.

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Gunawan, S., Azarm, S. Multi-objective robust optimization using a sensitivity region concept. Struct Multidisc Optim 29, 50–60 (2005). https://doi.org/10.1007/s00158-004-0450-8

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  • DOI: https://doi.org/10.1007/s00158-004-0450-8

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