Reliability-based multiobjective design optimization under interval uncertainty

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Journal Article
CMES - Computer Modeling in Engineering and Sciences, 2011, 74 (1), pp. 39 - 64
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This paper studies the reliability-based multiobjective optimization by using a new interval strategy to model uncertain parameters. A new satisfaction degree of interval, which is significantly extended from [0, 1] to [-∞, +∞], is introduced into the non-probabilistic reliability-based optimization. Based on a predefined satisfaction degree level, the uncertain constraints can be effectively transformed into deterministic ones. The interval number programming method is applied to change each uncertain objective function to a deterministic two-objective optimization. So in this way the uncertain multiobjective optimization problem is transformed into a deterministic optimization problem and a reliability-based multiobjective optimization is then established. For sophisticated engineering problems, the objectives and constraints are modeled by using the response surface (RS) approximation method to improve the optimization efficiency. Thus the reliabilitybased multiobjective optimization is combined with the RS approximation models to form an approximation optimization problem. For the multiobjective optimization, the Pareto sets can be obtained with different satisfactory degree levels. Two numerical examples and one real-world crashworthiness design for vehicle frontal structure are presented to demonstrate the effectiveness of the proposed approach. Copyright © 2011 Tech Science Press.
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