A deep instance generative framework for milp solvers under limited data availability
In the past few years, there has been an explosive surge in the use of machine learning (ML)
techniques to address combinatorial optimization (CO) problems, especially mixed-integer …
techniques to address combinatorial optimization (CO) problems, especially mixed-integer …
[图书][B] Integer programming
LA Wolsey - 2020 - books.google.com
A PRACTICAL GUIDE TO OPTIMIZATION PROBLEMS WITH DISCRETE OR INTEGER
VARIABLES, REVISED AND UPDATED The revised second edition of Integer Programming …
VARIABLES, REVISED AND UPDATED The revised second edition of Integer Programming …
Tight and compact MILP formulation for the thermal unit commitment problem
G Morales-España, JM Latorre… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
This paper presents a mixed-integer linear programming (MILP) reformulation of the thermal
unit commitment (UC) problem. The proposed formulation is simultaneously tight and …
unit commitment (UC) problem. The proposed formulation is simultaneously tight and …
Mixed integer linear programming formulation techniques
JP Vielma - Siam Review, 2015 - SIAM
A wide range of problems can be modeled as Mixed Integer Linear Programming (MIP)
problems using standard formulation techniques. However, in some cases the resulting MIP …
problems using standard formulation techniques. However, in some cases the resulting MIP …
[HTML][HTML] Progress in mathematical programming solvers from 2001 to 2020
This study investigates the progress made in lp and milp solver performance during the last
two decades by comparing the solver software from the beginning of the millennium with the …
two decades by comparing the solver software from the beginning of the millennium with the …
Mixed integer programming: Analyzing 12 years of progress
T Achterberg, R Wunderling - Facets of combinatorial optimization …, 2013 - Springer
Back in 2001, Bixby et al.(The Sharpest Cut: The Impact of Manfred Padberg and His Work,
pp. 309–325, 2004) provided an analysis of the performance impact of the main mixed …
pp. 309–325, 2004) provided an analysis of the performance impact of the main mixed …
Learning to select cuts for efficient mixed-integer programming
Cutting plane methods play a significant role in modern solvers for tackling mixed-integer
programming (MIP) problems. Proper selection of cuts would remove infeasible solutions in …
programming (MIP) problems. Proper selection of cuts would remove infeasible solutions in …
A simple effective heuristic for embedded mixed-integer quadratic programming
In this paper, we propose a fast optimisation algorithm for approximately minimising convex
quadratic functions over the intersection of affine and separable constraints (ie the Cartesian …
quadratic functions over the intersection of affine and separable constraints (ie the Cartesian …
Presolve reductions in mixed integer programming
T Achterberg, RE Bixby, Z Gu… - INFORMS Journal …, 2020 - pubsonline.informs.org
Mixed integer programming has become a very powerful tool for modeling and solving real-
world planning and scheduling problems, with the breadth of applications appearing to be …
world planning and scheduling problems, with the breadth of applications appearing to be …
Learning cut selection for mixed-integer linear programming via hierarchical sequence model
Cutting planes (cuts) are important for solving mixed-integer linear programs (MILPs), which
formulate a wide range of important real-world applications. Cut selection--which aims to …
formulate a wide range of important real-world applications. Cut selection--which aims to …