An Improved Initial Population Strategy for Compliant Mechanism Designs Using Evolutionary Optimization

In this paper, an improved initial random population strategy using a binary (0–1) representation of continuum structures is developed for evolving the topologies of path generating complaint mechanism. It helps the evolutionary optimization procedure to start with the structures which are free from impracticalities such as ‘checker-board’ pattern and disconnected ‘floating’ material. For generating an improved initial population, intermediate points are created randomly and the support, loading and output regions of a structure are connected through these intermediate points by straight lines. Thereafter, a material is assigned to those grids only where these straight lines pass. In the present study, single and two-objective optimization problems are solved using a local search based evolutionary optimization (NSGA-II) procedure. The single objective optimization problem is formulated by minimizing the weight of structure and a two-objective optimization problem deals with the simultaneous minimization of weight and input energy supplied to the structure. In both cases, an optimization problem is subjected to constraints limiting the allowed deviation at each precision point of a prescribed path so that the task of generating a user-defined path is accomplished and limiting the maximum stress to be within the allowable strength of material. Non-dominated solutions obtained after NSGA-II run are further improved by a local search procedure. Motivation behind the two-objective study is to find the trade-off optimal solutions so that diverse non-dominated topologies of complaint mechanism can be evolved in one run of optimization procedure. The obtained results of two-objective optimization study is compared with an usual study in which material in each grid is assigned at random for creating an initial population of continuum structures. Due to the use of improved initial population, the obtained non-dominated solutions outperform that of the usual study. Different shapes and nature of connectivity of the members of support, loading and output regions of the non-dominated solutions are evolved which will allow the designers to understand the topological changes which made the trade-off and will be helpful in choosing a particular solution for practice.Copyright © 2008 by ASME

[1]  Ren-Jye Yang,et al.  Optimal topology design using linear programming , 1994 .

[2]  Estrella Veguería,et al.  A simple evolutionary topology optimization procedure for compliant mechanism design , 2007 .

[3]  Patrick V. Hull,et al.  Optimal synthesis of compliant mechanisms using subdivision and commercial FEA , 2006 .

[4]  Kwun-Lon Ting,et al.  Topological Synthesis of Compliant Mechanisms Using Spanning Tree Theory , 2005 .

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

[6]  Philippe Bidaud,et al.  A new compliant mechanism design methodology based on flexible building blocks , 2004, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

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

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

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

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

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

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

[13]  R. Parsons,et al.  Developing genetic programming techniques for the design of compliant mechanisms , 2002 .

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

[15]  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).

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

[17]  Noboru Kikuchi,et al.  TOPOLOGY OPTIMIZATION OF COMPLIANT MECHANISMS USING THE HOMOGENIZATION METHOD , 1998 .

[18]  Sridhar Kota,et al.  Topology and Dimensional Synthesis of Compliant Mechanisms Using Discrete Optimization , 2006 .

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

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

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

[22]  M. Bendsøe,et al.  Generating optimal topologies in structural design using a homogenization method , 1988 .

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

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

[25]  Kalyanmoy Deb,et al.  A domain-specific crossover and a helper objective for generating minimum weight compliant mechanisms , 2008, GECCO '08.

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

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

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

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

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