A review and comparison of solvers for convex MINLP
In this paper, we present a review of deterministic software for solving convex MINLP
problems as well as a comprehensive comparison of a large selection of commonly …
problems as well as a comprehensive comparison of a large selection of commonly …
Branch-and-bound algorithms: A survey of recent advances in searching, branching, and pruning
DR Morrison, SH Jacobson, JJ Sauppe, EC Sewell - Discrete Optimization, 2016 - Elsevier
The branch-and-bound (B&B) algorithmic framework has been used successfully to find
exact solutions for a wide array of optimization problems. B&B uses a tree search strategy to …
exact solutions for a wide array of optimization problems. B&B uses a tree search strategy to …
Exact combinatorial optimization with graph convolutional neural networks
Combinatorial optimization problems are typically tackled by the branch-and-bound
paradigm. We propose a new graph convolutional neural network model for learning branch …
paradigm. We propose a new graph convolutional neural network model for learning branch …
Learning certifiably optimal rule lists for categorical data
We present the design and implementation of a custom discrete optimization technique for
building rule lists over a categorical feature space. Our algorithm produces rule lists with …
building rule lists over a categorical feature space. Our algorithm produces rule lists with …
3D deployment of multiple UAV-mounted base stations for UAV communications
Recently, unmanned aerial vehicles (UAVs) have attracted lots of attention because of their
high mobility and low cost. This article investigates a communication system assisted by …
high mobility and low cost. This article investigates a communication system assisted by …
Learning to branch in mixed integer programming
The design of strategies for branching in Mixed Integer Programming (MIP) is guided by
cycles of parameter tuning and offline experimentation on an extremely heterogeneous …
cycles of parameter tuning and offline experimentation on an extremely heterogeneous …
Hybrid models for learning to branch
Abstract A recent Graph Neural Network (GNN) approach for learning to branch has been
shown to successfully reduce the running time of branch-and-bound algorithms for Mixed …
shown to successfully reduce the running time of branch-and-bound algorithms for Mixed …
[HTML][HTML] A modeler's guide to handle complexity in energy systems optimization
Determining environmentally-and economically-optimal energy systems designs and
operations is complex. In particular, the integration of weather-dependent renewable energy …
operations is complex. In particular, the integration of weather-dependent renewable energy …
Mixed-integer nonlinear optimization
Many optimal decision problems in scientific, engineering, and public sector applications
involve both discrete decisions and nonlinear system dynamics that affect the quality of the …
involve both discrete decisions and nonlinear system dynamics that affect the quality of the …
A survey of variants and extensions of the location-routing problem
M Drexl, M Schneider - European journal of operational research, 2015 - Elsevier
This is a review of the literature on variants and extensions of the standard location-routing
problem published since the last survey, by Nagy and Salhi, appeared in 2006. We propose …
problem published since the last survey, by Nagy and Salhi, appeared in 2006. We propose …