Project
AA-Mobil-1
Solution techniques for Mixed-Integer Nonconvex Optimization
Project Heads
Mathieu Besançon, Sebastian Pokutta
Project Members
Deborah Hendrych
Project Duration
01.04.2026 – 31.03.2029
Located at
ZIB
Description
The project will investigate two main approaches:
(1) Automatic Convexification – developing systematic methods to add polynomial terms to objective functions that preserve optimal solutions while making problems more tractable, extending techniques from binary to general integer cases; and
(2) Spatial Branching – integrating advanced branching strategies with partial convexification to handle broader problem classes, including parallelization of bound computations and leveraging existing techniques like warm-starting and early termination to improve computational efficiency.
The overall goal is to create a comprehensive framework that balances convexification benefits with computational performance through strategic partial convexification and enhanced branching methods.
Project Webpages
Related Publications
Hendrych, Deborah, Hannah Troppens, Mathieu Besançon, and Sebastian Pokutta. “Convex integer optimization with Frank-Wolfe methods.” Mathematical Programming Computation, 17(4), 731–757. DOI: 10.1007/s12532-025-00288-w
Mexi, Gioni, Hendrych, Deborah, Designolle, Sebastién, Besançon, Mathieu, and Pokutta, Sebastian. “A Frank-Wolfe-based Primal Heuristic for Quadratic Mixed-integer Optimization.” arXiv preprint arXiv:2508.01299 (2025)
Software Repositories
The MINLP solver Boscia.jl is available under https://github.com/ZIB-IOL/Boscia.jl/tree/main and from the Julia registry.
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