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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 451–500 of 1277 papers

TitleStatusHype
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNetsCode1
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
Local Energy Distribution Based Hyperparameter Determination for Stochastic Simulated AnnealingCode0
LayerNAS: Neural Architecture Search in Polynomial Complexity—0
Genetic Algorithm Based Combinatorial Optimization for the Optimal Design of Water Distribution Network of Gurudeniya Service Zone, Sri Lanka—0
Quantum Annealing for Single Image Super-Resolution—0
RELS-DQN: A Robust and Efficient Local Search Framework for Combinatorial Optimization—0
Doubly Stochastic Matrix Models for Estimation of Distribution Algorithms—0
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time WindowsCode1
Low-rank combinatorial optimization and statistical learning by spatial photonic Ising machine—0
Quantum approximate optimization via learning-based adaptive optimizationCode1
Graph Neural Networks for the Offline Nanosatellite Task Scheduling ProblemCode0
RLOR: A Flexible Framework of Deep Reinforcement Learning for Operation ResearchCode1
Training Deep Boltzmann Networks with Sparse Ising Machines—0
Redrawing attendance boundaries to promote racial and ethnic diversity in elementary schools—0
Material Identification From Radiographs Without Energy Resolution—0
Solving routing problems for multiple cooperative Unmanned Aerial Vehicles using Transformer networks, vol. 122, pp. 106085, 2023Code0
Rolling Horizon based Temporal Decomposition for the Offline Pickup and Delivery Problem with Time WindowsCode0
Neural Airport Ground HandlingCode1
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural NetworksCode1
Evolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits—0
ASP: Learn a Universal Neural Solver!Code1
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization—0
Finding Support Examples for In-Context Learning—0
Learning Large Neighborhood Search for Vehicle Routing in Airport Ground HandlingCode1
Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture—0
Automated Graph Genetic Algorithm based Puzzle Validation for Faster Game Design—0
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial OptimizationCode2
Graph Adversarial Immunization for Certifiable RobustnessCode0
Expediting Distributed DNN Training with Device Topology-Aware Graph Deployment—0
A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms—0
Digging Deeper: Operator Analysis for Optimizing Nonlinearity of Boolean Functions—0
Nonlinear Random Matrices and Applications to the Sum of Squares Hierarchy—0
Approximately Optimal Core Shapes for Tensor Decompositions—0
Learning-based Online Optimization for Autonomous Mobility-on-Demand Fleet ControlCode0
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems—0
Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set—0
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning—0
Differentiating Through Integer Linear Programs with Quadratic Regularization and Davis-Yin SplittingCode0
DeciLS-PBO: an Effective Local Search Method for Pseudo-Boolean OptimizationCode0
Learning To Dive In Branch And Bound—0
Two-Stage Learning For the Flexible Job Shop Scheduling Problem—0
Flex-Net: A Graph Neural Network Approach to Resource Management in Flexible Duplex NetworksCode0
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