An Introduction to Development and Applications of Mixed-integer Linear Programming Solvers
Reporter:
Dr. Akang Wang, Research Scientist, General Solver Laboratory, Shenzhen Research Institute of Big Data
Inviter:
Chensong Zhang, Associate Professor
Subject:
An Introduction to Development and Applications of Mixed-integer Linear Programming Solvers
Time and place:
19:30-20:30 September 14(Wednesday), Tencent Meeting ID: 463-7874-0598
Abstract:
Many decision-making problems in practice can be formulated as monolithic mathematical models (e.g., mixed-integer linear programs), which are ready to be addressed by commercial optimization solvers (e.g., Gurobi, COPT). In this talk, I will first focus on the development of a linear programming solver, the key module of a mixed-integer linear programming (MILP) solver and its reliance on linear solvers. I will then share our efforts of utilizing classic methods to solve MILP problems in NeurIPS 2021 ML4CO competition. Furthermore, I will cover our recent work in a popular topic “learning to optimize”, e.g., using machine learning techniques to tackle MILP problems.