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Book ChapterDOI

A Suggested Extension of Special Ordered Sets to Non-Separable Non-Convex Programming Problems*

J.A. Tomlin
- 01 Jan 1981 - 
- Vol. 59, pp 359-370
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TLDR
In this article, a branch and bound method for solving non-separable non-convex programming problems where the nonlinearities are piecewise linearly approximated using the standard simplicial subdivision of the hypercube is proposed.
Abstract
This paper suggests a branch and bound method for solving non-separable non-convex programming problems where the nonlinearities are piecewise linearly approximated using the standard simplicial subdivision of the hypercube. The method is based on the algorithm for Special Ordered Sets, used with separable problems, but involves using two different types of branches to achieve valid approximations.

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Citations
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Journal ArticleDOI

Mixed-integer nonlinear optimization

TL;DR: An emerging area of mixed-integer optimal control that adds systems of ordinary differential equations to MINLP is described and a range of approaches for tackling this challenging class of problems are discussed, including piecewise linear approximations, generic strategies for obtaining convex relaxations for non-convex functions, spatial branch-and-bound methods, and a small sample of techniques that exploit particular types of non- Convex structures to obtain improved convex Relaxations.
Journal ArticleDOI

Non-convex mixed-integer nonlinear programming: A survey

TL;DR: In this paper, the authors survey the literature on non-convex mixed-integer nonlinear programs, discussing applications, algorithms, and software, and special attention is paid to the case in which the objective and constraint functions are quadratic.
Journal ArticleDOI

Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions

TL;DR: This work reviews several new and existing MIP formulations for continuous piecewise-linear functions with special attention paid to multivariate nonseparable functions.
Journal ArticleDOI

Mixed integer models for the stationary case of gas network optimization

TL;DR: This work describes techniques for a piece-wise linear approximation of the nonlinearities in this model resulting in a large mixed integer linear program and shows that the number of vertices is computationally tractable yielding exact separation algorithms.
Journal ArticleDOI

Modeling disjunctive constraints with a logarithmic number of binary variables and constraints

TL;DR: It is proved that the new formulations for piecewise linear functions of one and two variables that use a number of binary variables and extra constraints logarithmic in the number of linear pieces of the functions have favorable tightness properties and can significantly outperform other mixed integer binary formulations.
References
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Book

Numerical Methods

Journal ArticleDOI

Large-scale linearly constrained optimization

TL;DR: An algorithm for solving large-scale nonlinear programs with linear constraints is presented, which combines efficient sparse-matrix techniques as in the revised simplex method with stable quasi-Newton methods for handling the nonlinearities.
Journal ArticleDOI

A Nonlinear Programming Technique for the Optimization of Continuous Processing Systems

TL;DR: A numerical example, a model construction example, and a description of a particular existing computer system are included in order to clarify the mode of operation of the method.
Journal ArticleDOI

Homotopies for computation of fixed points

TL;DR: Given a point to set mapf on a simplex with certain conditions, an algorithm for computing fixed points is described, which operates by following the fixed point as an initially affine function is deformed towardsf.
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