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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 526–550 of 1277 papers

TitleStatusHype
A Survey for Solving Mixed Integer Programming via Machine Learning—0
Algoritmos Genéticos Aplicado ao Problema de Roteamento de Veículos—0
Accelerating Diffusion-based Combinatorial Optimization Solvers by Progressive Distillation—0
A 2-approximation algorithm for the softwired parsimony problem on binary, tree-child phylogenetic networks—0
HyColor: An Efficient Heuristic Algorithm for Graph Coloring—0
IA-GM: A Deep Bidirectional Learning Method for Graph Matching—0
Data-driven Prediction of Relevant Scenarios for Robust Combinatorial Optimization—0
On a class of data-driven mixed-integer programming problems under uncertainty: a distributionally robust approach—0
Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks—0
Assortment Planning with Sponsored Products—0
DAN: Decentralized Attention-based Neural Network for the MinMax Multiple Traveling Salesman Problem—0
Algorithms Inspired by Nature: A Survey—0
How Multimodal Integration Boost the Performance of LLM for Optimization: Case Study on Capacitated Vehicle Routing Problems—0
Assessment of Reinforcement Learning Algorithms for Nuclear Power Plant Fuel Optimization—0
Box Facets and Cut Facets of Lifted Multicut Polytopes—0
Assessing and Enhancing Graph Neural Networks for Combinatorial Optimization: Novel Approaches and Application in Maximum Independent Set Problems—0
Algorithm Discovery With LLMs: Evolutionary Search Meets Reinforcement Learning—0
Active Screening for Recurrent Diseases: A Reinforcement Learning Approach—0
How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods—0
Currency Arbitrage Optimization using Quantum Annealing, QAOA and Constraint Mapping—0
A Spectral Method for Unsupervised Multi-Document Summarization—0
Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approach—0
CreDes: Causal Reasoning Enhancement and Dual-End Searching for Solving Long-Range Reasoning Problems using LLMs—0
High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware—0
A Simulated Annealing-Based Multiobjective Optimization Algorithm for Minimum Weight Minimum Connected Dominating Set Problem—0
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