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Mathematical Optimization

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Mathematical Optimization

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Research Frontiers in Integer and Combinatorial Optimization

Exact and approximate algorithms for discrete optimization problems including integer programming and NP-hard combinatorial problems.

Symmetry Breaking in Combinatorial Search Trees
Polyhedral Geometry of NP-Hard Problem Landscapes
Learning-Augmented Branch-and-Bound Algorithms
Quantum-Classical Hybrid Integer Programming
Approximation Hardness at Combinatorial Phase Transitions
Dynamic Programming with Submodular Structure
Constraint Relaxations and LP Bounds Prediction
Symmetry-Aware Cutting Planes for Permutation Problems
Warm-Started Optimization via Neural Priors
Lattice-Based Approaches to Facility Location Problems

All Mathematical Optimization PhD categories