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Journal of Applied Mathematics
Volume 2015, Article ID 165601, 12 pages
http://dx.doi.org/10.1155/2015/165601
Research Article

Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm

1K.L.N College of Engineering, Pottapalayam 630611, India
2Sri Krishna College of Technology, Coimbatore 641 042, India

Received 17 October 2014; Revised 8 January 2015; Accepted 8 January 2015

Academic Editor: Zong Woo Geem

Copyright © 2015 P. Sabarinath et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms.