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Comparisons of Break Points Selection Strategies for Piecewise Linear Approximation

Ming-Hua Lin1 and Jung-Fa Tsai2
1.Department of Information Technology and Management, Shih Chien University, Taipei 10462, Taiwan
2.Department of Business Management, National Taipei University of Technology, Taipei 10608, Taiwan

Abstract—Many optimization approaches adopt piecewise linear functions to solve real applications that are formulated as nonlinear programming problems. The number of the break points and the positions of the break points are two major factors that affect the quality of the linear approximation. Most of existing methods select evenly-spaced break points for constructing a piecewise linear approximation of a nonlinear function. This study investigates the impact of different break points selection strategies on the accuracy of the linear approximation. Two numerical experiments are presented to compare the performance of different break points selection strategies in solving nonlinear programming problems.

Index Terms—global optimization, break point selection, piecewise linear function

Cite: Ming-Hua Lin and Jung-Fa Tsai, "Comparisons of Break Points Selection Strategies for Piecewise Linear Approximation," International Journal of Mechanical Engineering and Robotics Research, Vol.4, No. 3, pp. 247-250, July 2015. DOI: 10.18178/ijmerr.4.3.247-250