A domain-specific crossover and a helper objective for generating minimum weight compliant mechanisms

While designing the Compliant Mechanisms (CM), an equal attention is required on both the problem formulation and the optimization algorithm used. Authors of this paper have successfully proposed the formulation of CM tracing user-defined paths based on the precision points. In this paper, authors modify the NSGA-II algorithm by incorporating (i) a helper objective and (ii) a domain specific crossover which assist in generating a diverse set of non-dominated solutions. First, the single-objective optimization problem of minimizing the weight of structure is solved and named the topology as a reference design. Thereafter, a bi-objective optimization problem is dealt to evolve 'trade-off' solutions for a primary objective of minimizing the weight and a secondary objective of maximizing the diversity with respect to the reference design. Both the optimization problems are solved using a local search based NSGA-II procedure. This study has further compared its results with another GA implementation having a different crossover operator.

[1]  A. Saxena,et al.  Synthesis of Path Generating Compliant Mechanisms Using Initially Curved Frame Elements , 2007 .

[2]  A. Saxena Synthesis of Compliant Mechanisms for Path Generation using Genetic Algorithm , 2005 .

[3]  M. Jakiela,et al.  Genetic algorithm-based structural topology design with compliance and topology simplification considerations , 1996 .

[4]  Eckart Zitzler,et al.  Evolutionary algorithms for multiobjective optimization: methods and applications , 1999 .

[5]  Kang Tai,et al.  Design of structures and compliant mechanisms by evolutionary optimization of morphological representations of topology , 2000 .

[6]  Kalyanmoy Deb,et al.  Towards generating diverse topologies of path tracing compliant mechanisms using a local search based multi-objective genetic algorithm procedure , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[7]  T. Ray,et al.  Design Synthesis of Path Generating Compliant Mechanisms by Evolutionary Optimization of Topology and Shape , 2002 .

[8]  Kang Tai,et al.  Target-matching test problem for multiobjective topology optimization using genetic algorithms , 2007 .

[9]  Kalyanmoy Deb,et al.  A Hybrid Multi-objective Evolutionary Approach to Engineering Shape Design , 2001, EMO.

[10]  K. Tai,et al.  Structural topology optimization using a genetic algorithm with a morphological geometric representation scheme , 2005 .

[11]  G. K. Ananthasuresh,et al.  Optimal Synthesis Methods for MEMS , 2003 .

[12]  Anupam Saxena,et al.  Topology design of large displacement compliant mechanisms with multiple materials and multiple output ports , 2005 .

[13]  K. Deb,et al.  Evolving Path Generation Compliant Mechanisms ( PGCM ) using Local-search based Multi-objective Genetic Algorithm , 2006 .

[14]  G. K. Ananthasuresh,et al.  Designing compliant mechanisms , 1995 .

[15]  Larry L. Howell,et al.  A Method for the Design of Compliant Mechanisms With Small-Length Flexural Pivots , 1994 .

[16]  Kalyanmoy Deb,et al.  Multiobjective Problem Solving from Nature: From Concepts to Applications (Natural Computing Series) , 2008 .

[17]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[18]  Kazuhiro Saitou,et al.  Genetic algorithms as an approach to configuration and topology design , 1994, DAC 1993.

[19]  M. Jakiela,et al.  Continuum structural topology design with genetic algorithms , 2000 .

[20]  Mark J. Jakiela,et al.  Generation and Classification of Structural Topologies With Genetic Algorithm Speciation , 1997 .

[21]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..