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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 551–575 of 1277 papers

TitleStatusHype
A Graph Multi-separator Problem for Image Segmentation—0
Large Language Models for Supply Chain Optimization—0
Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization—0
Explainable quantum regression algorithm with encoded data structure—0
Learning to Branch in Combinatorial Optimization with Graph Pointer Networks—0
A Formal Perspective on Byte-Pair EncodingCode0
Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and ApplicationsCode0
Object Detection based on the Collection of Geometric Evidence—0
TreeDQN: Learning to minimize Branch-and-Bound treeCode0
Minimizing Energy Consumption in MU-MIMO via Antenna Muting by Neural Networks with Asymmetric Loss—0
Policy-Based Self-Competition for Planning ProblemsCode0
Dynamic Programming on a Quantum Annealer: Solving the RBC ModelCode0
Learning-Based Heuristic for Combinatorial Optimization of the Minimum Dominating Set Problem using Graph Convolutional NetworksCode0
Barriers for the performance of graph neural networks (GNN) in discrete random structures. A comment on~schuetz2022combinatorial,angelini2023modern,schuetz2023reply—0
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial OptimizationCode0
Dynamic Algorithms for Matroid Submodular Maximization—0
Clustering Method for Time-Series Images Using Quantum-Inspired Computing Technology—0
The First Proven Performance Guarantees for the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) on a Combinatorial Optimization Problem—0
Neural Bee Colony Optimization: A Case Study in Public Transit Network Design—0
Efficient Training of Multi-task Combinarotial Neural Solver with Multi-armed Bandits—0
Assessment of Reinforcement Learning Algorithms for Nuclear Power Plant Fuel Optimization—0
Near-Optimal LOS and Orientation Aware Intelligent Reflecting Surface Placement—0
Quantum-Based Combinatorial Optimization for Optimal Sensor Placement in Civil Structures—0
New Characterizations and Efficient Local Search for General Integer Linear Programming—0
Monotone comparative statics for submodular functions, with an application to aggregated deferred acceptance—0
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