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A domain-specific crossover and a helper objective for generating minimum weight compliant mechanisms
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation table of contents
Atlanta, GA, USA
POSTER SESSION: Real-world application posters table of contents
Pages 1723-1724  
Year of Publication: 2008
ISBN:978-1-60558-130-9
Authors
Deepak Sharma  Indian Institute of Technology Kanpur, Kanpur, U.P., India
Kalyanmoy Deb  Indian Institute of Technology Kanpur, Kanpur, U.P., India
N. N. Kishore  Indian Institute of Technology Kanpur, Kanpur, U.P., India
Sponsors
ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
Publisher
ACM  New York, NY, USA
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ABSTRACT

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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan. A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2):182--197, 2002.
 
2
K. Deb and S. Chaudhuri. Automated discovery of innovative designs of mechanical components using evolutionary multiobjective algorithms. In N. Nedjah and L. de Macedo M, editors, Evolutionary Machine Design: Methodology and Applications, chapter 6, pages 143--168. Nova Science Publishers, Inc, New York, 2005.
 
3
D. Sharma, K. Deb, and N. N. Kishore. Evolving path generation compliant mechanisms (PGCM) using local-search based multi-objective genetic algorithm. In International Conference on Trends in Product Life Cycle, Modeling, Simulation and Synthesis (PLMSS), pages 227--238, December 2006.
 
4
D. Sharma, K. Deb, and N. N. Kishore. A domain-specific crossover and a helper objective for generating minimum weight compliant mechanisms. Technical Report KanGAL Report No.2008001., Indian Institute of Technology Kanpur, India, 2008.
 
5
D. Sharma, K. Deb, and N. N. Kishore. Towards generating diverse topologies of path tracing compliant mechanisms using a local search based multi-objective genetic algorithm procedure. Accepted in 2008 IEEE World Congress on Computational Intelligence (WCCI) Conference, 2008.

Collaborative Colleagues:
Deepak Sharma: colleagues
Kalyanmoy Deb: colleagues
N. N. Kishore: colleagues