Piecewise linearization of bivariate nonlinear functions: minimizing the number of pieces under a bounded approximation error

DOI10.1007/978-3-031-18530-4_9zbMath1528.90215OpenAlexW4223454435MaRDI QIDQ6166895

Sandra Ulrich Ngueveu, Aloïs Duguet

Publication date: 3 August 2023

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-031-18530-4_9

zbMATH Keywords

heuristicsmixed integer nonlinear programmingpiecewise linear approximationbivariate nonlinear functions

Mathematics Subject Classification ID

Mixed integer programming (90C11) Approximation methods and heuristics in mathematical programming (90C59) Combinatorial optimization (90C27)

Related Items (3)

A linear programming approach to difference-of-convex piecewise linear approximation ⋮ A unified framework for bivariate clustering and regression problems via mixed-integer linear programming ⋮ Piecewise linearization of bivariate nonlinear functions: minimizing the number of pieces under a bounded approximation error

Cites Work

• Fitting piecewise linear continuous functions
• Continuous piecewise linear delta-approximations for bivariate and multivariate functions
• On the number of segments needed in a piecewise linear approximation
• Piecewise linear bounding of univariate nonlinear functions and resulting mixed integer linear programming-based solution methods
• Using Piecewise Linear Functions for Solving MINLPs
• Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions
• Piecewise Linear Function Fitting via Mixed-Integer Linear Programming
• Piecewise linearization of bivariate nonlinear functions: minimizing the number of pieces under a bounded approximation error

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