A new multi-objective programming scheme for topology optimization of compliant mechanisms
- Publication Type:
- Journal Article
- Citation:
- Structural and Multidisciplinary Optimization, 2010, 40 (1-6), pp. 241 - 255
- Issue Date:
- 2010-01-01
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This paper presents an alternative method in implementing multi-objective optimization of compliant mechanisms in the field of continuum-type topology optimization. The method is designated as "SIMP-PP" and it achieves multi-objective topology optimization by merging what is already a mature topology optimization method-solid isotropic material with penalization (SIMP) with a variation of the robust multi-objective optimization method-physical programming (PP). By taking advantages of both sides, the combination causes minimal variation in computation algorithm and numerical scheme, yet yields improvements in the multi-objective handling capability of topology optimization. The SIMP-PP multi-objective scheme is introduced into the systematic design of compliant mechanisms. The final optimization problem is formulated mathematically using the aggregate objective function which is derived from the original individual design objectives with PP, subjected to the specified constraints. A sequential convex programming method, the method of moving asymptotes (MMA) is then utilized to process the optimization evolvement based on the design sensitivity analysis. The main findings in this study include distinct advantages of the SIMP-PP method in various aspects such as computation efficiency, adaptability in convex and non-convex multi-criteria environment, and flexibility in problem formulation. Observations are made regarding its performance and the effect of multi-objective optimization on the final topologies. In general, the proposed SIMP-PP method is an appealing multi-objective topology optimization scheme suitable for "real world" problems, and it bridges the gap between standard topological design and multi-criteria optimization. The feasibility of the proposed topology optimization method is exhibited by benchmark examples. © 2009 Springer-Verlag.
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