Solving mixed-integer nonlinear programmes using adaptively refined mixed-integer linear programmes
From MaRDI portal
Publication:4972544
DOI10.1080/10556788.2018.1556661zbMath1432.90089OpenAlexW2899498410WikidataQ128573024 ScholiaQ128573024MaRDI QIDQ4972544
Lars Schewe, Robert Burlacu, Björn Geissler
Publication date: 25 November 2019
Published in: Optimization Methods and Software (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10556788.2018.1556661
global optimizationadaptivitypiecewise linear approximationmixed-integer nonlinear programminggas transport optimization
Related Items
The cost of not knowing enough: mixed-integer optimization with implicit Lipschitz nonlinearities ⋮ The decomposition-based outer approximation algorithm for convex mixed-integer nonlinear programming ⋮ Data-driven mixed-integer linear programming-based optimisation for efficient failure detection in large-scale distributed systems ⋮ A linear programming approach to difference-of-convex piecewise linear approximation ⋮ Adaptive piecewise linear relaxations for enclosure computations for nonconvex multiobjective mixed-integer quadratically constrained programs ⋮ On piecewise linear approximations of bilinear terms: structural comparison of univariate and bivariate mixed-integer programming formulations ⋮ Data-driven stochastic optimization for distributional ambiguity with integrated confidence region ⋮ A decomposition method for MINLPs with Lipschitz continuous nonlinearities ⋮ Maximizing the storage capacity of gas networks: a global MINLP approach ⋮ Properties, extensions and application of piecewise linearization for Euclidean norm optimization in \(\mathbb{R}^2\) ⋮ Non-convex nested Benders decomposition ⋮ On refinement strategies for solving \(\textsc{MINLP}\)s by piecewise linear relaxations: a generalized red refinement ⋮ On generalized surrogate duality in mixed-integer nonlinear programming
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Optimistic MILP modeling of non-linear optimization problems
- A reformulation framework for global optimization
- Modeling disjunctive constraints with a logarithmic number of binary variables and constraints
- Continuous piecewise linear delta-approximations for bivariate and multivariate functions
- Continuous piecewise linear delta-approximations for univariate functions: computing minimal breakpoint systems
- Piecewise-linear approximations of multidimensional functions
- Location, scheduling, design and integer programming
- Approximating separable nonlinear functions via mixed zero-one programs
- A polyhedral branch-and-cut approach to global optimization
- A lower bound for the simplexity of the \(n\)-cube via hyperbolic volumes
- Mixed integer models for the stationary case of gas network optimization
- MINLPLib—A Collection of Test Models for Mixed-Integer Nonlinear Programming
- Using Piecewise Linear Functions for Solving MINLPs
- Evaluating Gas Network Capacities
- An Exact Rational Mixed-Integer Programming Solver
- Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions
- On the Solution of Discrete Programming Problems
- Analysis of MILP Techniques for the Pooling Problem
- Computational Geometry in C
- A Convergent Adaptive Algorithm for Poisson’s Equation
- Solving Highly Detailed Gas Transport MINLPs: Block Separability and Penalty Alternating Direction Methods
- A New Algorithm for MINLP Applied to Gas Transport Energy Cost Minimization
- Mixed-integer nonlinear optimization
- Chapter 6: The MILP-relaxation approach
- Chapter 12: Computational results for validation of nominations
- Polyhedral methods for piecewise-linear functions. I: The lambda method
- Benchmarking optimization software with performance profiles.
This page was built for publication: Solving mixed-integer nonlinear programmes using adaptively refined mixed-integer linear programmes
