Multi-objective robust topology optimization with dynamic weighting

Mike Riley, Peter D Dunning, Christopher J Brampton, H Alicia Kim

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution


A common robust topology optimization is formulated as a weighted sum of expected and variance of the objective functions for the given uncertainties. This has recently been applied to topology optimization with uncertainties in loading, [1]. Figure 1(a) shows the Pareto front of solutions found using uniformly distributed weightings. This front suffers from crowding for weight values < 0.5 and is sparsely populated for weights > 0.625. In the general case, the two goals of multi-objective optimization are; to find the most diverse set of Pareto optimal solutions, and, to discover solutions as close as possible to the true Pareto front. This paper presents schemes to achieve both these goals.
Original languageEnglish
Title of host publicationInternational Conference on Engineering and Applied Sciences Optimization
Publication statusPublished - 4 Jun 2014


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