I am excited to chair two sessions at the 2024
@INFORMS Annual Meeting in Seattle! Join us to explore the latest advancements in optimization techniques and their applications.
Session 1:
Title: Advanced Optimization for Mixed Integer Programming
Date/Time: Monday, October 21, 12:45 PM - 2:00 PM
Venue: Regency - 709
Speakers:
Peng Zhang, Stony Brook University - Enhancing Quantum Optimization Scalability: A Singular Transformation Approach to Unit Commitment
Luke Marshall, Microsoft - Accelerating Branch-and-Price via Template Pricing
Hubert Missbauer, University of Innsbruck - Using Lagrangian Decomposition to Coordinate Order Release Planning and Production Scheduling
Mikhail Bragin, Southern California Edison - Acceleration of Level Adjustment for the Polyak Stepsize: Applications to Mixed Integer Programming
Session 2:
Title: Recent Advancements in Accelerated Optimization
Date/Time: Tuesday, October 22, 4:00 PM - 5:15 PM
Venue: Summit - 423
Speakers:
Peijing Liu, University of Southern California - Polyhedral Analysis of Quadratic Optimization Problems with Stieltjes Matrices and Indicators
Tao Jiang, Cornell University - A Linearly Convergent Gauss-Newton Subgradient Method for Ill-Conditioned Problems
Xinyao Zhang, University of Southern California - Indefinite Quadratic Programs and Complementarity Constraints by a Progressive MIP Method
Berkay Becu, Georgia Institute of Technology - A Machine Learning Approach for Rank-1 GMI Cuts
Looking forward to deepening our collective understanding of optimization and its future directions! @informs2024
#INFORMS2024 #Optimization #MIP #MixedIntegerProgramming #AcceleratedOptimization #Research #OperationsResearch #QuantumOptimization