Optimal breakpoint selection method for piecewise linear approximation

Fuente: arXiv
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Main Author: Liu, Shaojun
Format: Preprint
Published: 2024
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author Liu, Shaojun
author_facet Liu, Shaojun
contents Piecewise linearization is a key technique for solving nonlinear problems in transportation network design and other optimization fields, in which generating breakpoints is a fundamental task. This paper proposes an optimal breakpoint selection method, rotational adjusting method (RAM), to minimize the approximation error between the original function and the piecewise linear function with limited number of pieces, applicable to both convex or concave function. RAM rotationally adjusts the location of breakpoints based on its adjacent breakpoints, and the optimal positions would be reached after several iterations. The optimality of the method is proved. Numerical experiments are conducted on the logarithmic function.
format Preprint
id arxiv_https___arxiv_org_abs_2407_21081
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal breakpoint selection method for piecewise linear approximation
Liu, Shaojun
Optimization and Control
Piecewise linearization is a key technique for solving nonlinear problems in transportation network design and other optimization fields, in which generating breakpoints is a fundamental task. This paper proposes an optimal breakpoint selection method, rotational adjusting method (RAM), to minimize the approximation error between the original function and the piecewise linear function with limited number of pieces, applicable to both convex or concave function. RAM rotationally adjusts the location of breakpoints based on its adjacent breakpoints, and the optimal positions would be reached after several iterations. The optimality of the method is proved. Numerical experiments are conducted on the logarithmic function.
title Optimal breakpoint selection method for piecewise linear approximation
topic Optimization and Control
url https://arxiv.org/abs/2407.21081