Abstract
This paper applies a genetic algorithm-based optimisation procedure, namely, NSGA-II, to the problem of synthesis of a four-bar mechanism. The internal parameters of \({\texttt{\rm NSGA-II}}\) are tuned using a Design of Experiments (DoE) procedure to enhance the quality of the final results. Constraints are handled through a penalty formulation. Further, a scaling function is introduced, which transforms the penalty terms in a manner that leads to faster convergence of the solutions. The theoretical developments are illustrated via applications to two well-studied problems in the domain of coupler-curve synthesis. A comparison of the results vis-a-vis existing ones shows that the proposed enhancements of the basic scheme of \({\texttt{\rm NSGA-II}}\) deliver promising improvements in terms of accuracy, and rate of convergence of the solutions.
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Badduri, J., Srivatsan, R.A., Kumar, G.S., Bandyopadhyay, S. (2012). Coupler-Curve Synthesis of a Planar Four-Bar Mechanism Using NSGA-II. In: Bui, L.T., Ong, Y.S., Hoai, N.X., Ishibuchi, H., Suganthan, P.N. (eds) Simulated Evolution and Learning. SEAL 2012. Lecture Notes in Computer Science, vol 7673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34859-4_46
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DOI: https://doi.org/10.1007/978-3-642-34859-4_46
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