no code implementations • 3 Feb 2023 • Taoan Huang, Aaron Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Integer Linear Programs (ILPs) are powerful tools for modeling and solving a large number of combinatorial optimization problems.
no code implementations • 15 Dec 2022 • Taoan Huang, Aaron Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
LNS relies on heuristics to select neighborhoods to search in.
no code implementations • 22 Oct 2022 • Aaron Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian
To bridge this gap, we propose SurCo that learns linear Surrogate costs which can be used by existing Combinatorial solvers to output good solutions to the original nonlinear combinatorial optimization problem, combining the flexibility of gradient-based methods with the structure of linear combinatorial optimization.
1 code implementation • 7 Sep 2022 • Sumedh Pendurkar, Taoan Huang, Sven Koenig, Guni Sharon
Our first experimental results for three representative NP-hard minimum-cost path problems suggest that using neural networks to approximate completely informed heuristic functions with high precision might result in network sizes that scale exponentially in the instance sizes.
no code implementations • 10 Dec 2020 • Taoan Huang, Bistra Dilkina, Sven Koenig
In this work, we propose an oracle for conflict selection that results in smaller search tree sizes than the one used in previous work.
no code implementations • NeurIPS Workshop LMCA 2020 • Taoan Huang, Bistra Dilkina, Sven Koenig
Multi-Agent Path Finding is an NP-hard problem that is difficult for current approaches to solve optimally.
no code implementations • 20 Jul 2019 • Taoan Huang, Bohui Fang, Xiaohui Bei, Fei Fang
Transportation service providers that dispatch drivers and vehicles to riders start to support both on-demand ride requests posted in real time and rides scheduled in advance, leading to new challenges which, to the best of our knowledge, have not been addressed by existing works.