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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 351–400 of 1277 papers

TitleStatusHype
Characterization of Locality in Spin States and Forced Moves for Optimizations—0
Towards the Inferrence of Structural Similarity of Combinatorial Landscapes—0
Pointer Networks Trained Better via Evolutionary Algorithms—0
Biased Random-Key Genetic Algorithms: A Review—0
A Bayesian approach for prompt optimization in pre-trained language models—0
TOP-Former: A Multi-Agent Transformer Approach for the Team Orienteering ProblemCode0
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement Learning—0
A Survey and Analysis of Evolutionary Operators for PermutationsCode0
Variational Annealing on Graphs for Combinatorial OptimizationCode1
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks—0
All-to-all reconfigurability with sparse and higher-order Ising machinesCode0
Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach—0
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization RegimeCode1
An Expandable Machine Learning-Optimization Framework to Sequential Decision-Making—0
RIGA: A Regret-Based Interactive Genetic Algorithm—0
Amplitude-Ensemble Quantum-Inspired Tabu Search Algorithm for Solving 0/1 Knapsack Problems—0
Computing with Residue Numbers in High-Dimensional Representation—0
Pointer Networks with Q-Learning for Combinatorial Optimization—0
Temporal Sequencing of DocumentsCode0
Addressing The Knapsack Challenge Through Cultural Algorithm Optimization—0
Unveiling the Limits of Learned Local Search Heuristics: Are You the Mightiest of the Meek?—0
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network—0
Large Language Models as Evolutionary OptimizersCode1
High-Dimensional Prediction for Sequential Decision Making—0
Interferometric Neural NetworksCode0
Neural Multi-Objective Combinatorial Optimization with Diversity EnhancementCode1
Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and PruningCode1
Neural Packing: from Visual Sensing to Reinforcement Learning—0
Exploring the Power of Graph Neural Networks in Solving Linear Optimization ProblemsCode1
On permutation symmetries in Bayesian neural network posteriors: a variational perspective—0
Enhancing Column Generation by Reinforcement Learning-Based Hyper-Heuristic for Vehicle Routing and Scheduling Problems—0
Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale GeneralizationCode1
Graph-SCP: Accelerating Set Cover Problems with Graph Neural NetworksCode0
GRASP: Accelerating Shortest Path Attacks via Graph Attention—0
Diversity from Human Feedback—0
An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems—0
Oracle Efficient Algorithms for Groupwise Regret—0
Routing Arena: A Benchmark Suite for Neural Routing Solvers—0
A Deep Instance Generative Framework for MILP Solvers Under Limited Data AvailabilityCode1
GenCO: Generating Diverse Designs with Combinatorial Constraints—0
Are Graph Neural Networks Optimal Approximation Algorithms?Code1
Too Big, so Fail? -- Enabling Neural Construction Methods to Solve Large-Scale Routing ProblemsCode0
Controlling Continuous Relaxation for Combinatorial OptimizationCode0
Genetic Engineering Algorithm (GEA): An Efficient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems—0
DeepACO: Neural-enhanced Ant Systems for Combinatorial OptimizationCode1
Enhancing Network Resilience through Machine Learning-powered Graph Combinatorial Optimization: Applications in Cyber Defense and Information Diffusion—0
QAL-BP: An Augmented Lagrangian Quantum Approach for Bin PackingCode0
Efficient LDPC Decoding using Physical Computation—0
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNetsCode1
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