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Combinatorial Optimization

Combinatorial Optimization is a category of problems which requires optimizing a function over a combination of discrete objects and the solutions are constrained. Examples include finding shortest paths in a graph, maximizing value in the Knapsack problem and finding boolean settings that satisfy a set of constraints. Many of these problems are NP-Hard, which means that no polynomial time solution can be developed for them. Instead, we can only produce approximations in polynomial time that are guaranteed to be some factor worse than the true optimal solution.

Source: Recent Advances in Neural Program Synthesis

Papers

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Showing 776–800 of 1277 papers

TitleStatusHype
Solving Graph-based Public Good Games with Tree Search and Imitation LearningCode0
An SMT Based Compositional Algorithm to Solve a Conflict-Free Electric Vehicle Routing Problem—0
Fair Disaster Containment via Graph-Cut Problems—0
Learning Pseudo-Backdoors for Mixed Integer Programs—0
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on GraphsCode1
Efficient Active Search for Combinatorial Optimization ProblemsCode1
Enhancing Robustness of Neural Networks through Fourier Stabilization—0
Noisy intermediate-scale quantum algorithm for semidefinite programmingCode1
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable ApproachCode1
Self-Supervision is All You Need for Solving Rubik's CubeCode1
Implicit MLE: Backpropagating Through Discrete Exponential Family DistributionsCode1
Experiments with graph convolutional networks for solving the vertex p-center problem—0
Policies for the Dynamic Traveling Maintainer Problem with Alerts—0
On a class of data-driven mixed-integer programming problems under uncertainty: a distributionally robust approach—0
Structural Causal Models Reveal Confounder Bias in Linear Program ModellingCode0
IA-GM: A Deep Bidirectional Learning Method for Graph Matching—0
Meta-Learning-Based Deep Reinforcement Learning for Multiobjective Optimization ProblemsCode1
Solve routing problems with a residual edge-graph attention neural networkCode1
Graph Learning: A Survey—0
Reconstruction of Convex Polytope Compositions from 3D Point-clouds—0
A Novel Surrogate-assisted Evolutionary Algorithm Applied to Partition-based Ensemble LearningCode0
Exact and Approximate Hierarchical Clustering Using A*—0
A Reinforcement Learning Environment For Job-Shop SchedulingCode1
Ecole: A Library for Learning Inside MILP SolversCode0
Distributed Deep Reinforcement Learning for Collaborative Spectrum Sharing—0
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