arXiv (All)
open access
A relax-fix-and-exclude algorithm for an MINLP problem with multilinear interpolations
This paper introduces a novel algorithm for Mixed-Integer Nonlinear Programming (MINLP) problems with multilinear interpolations of look-up tables. These problems arise when objective or constraints contain black-box functions only known at a finite set of evaluations on a predefined grid. We derive
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Optimization Methods#3505
- Predictive Dual Smoothing for Column Generation#1128998
- Linear equations with min and max operators: Computational complexity#1066556
- Linear Algebra and Optimization with Applications to Machine Learning - Volume II: Fundamentals of Optimization Theory with Applications to Machine Learning#489445
- Computational Nonsmooth Optimization#429979
Record · ID 1012000
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive