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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 76–100 of 1277 papers

TitleStatusHype
A Learning-based Iterative Method for Solving Vehicle Routing ProblemsCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionCode1
Automatic Truss Design with Reinforcement LearningCode1
A Bayesian algorithm for retrosynthesisCode1
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming ProblemCode1
Belief Propagation Neural NetworksCode1
BILP-Q: Quantum Coalition Structure GenerationCode1
Quantum approximate optimization via learning-based adaptive optimizationCode1
Exact Combinatorial Optimization with Graph Convolutional Neural NetworksCode1
A Deep Instance Generative Framework for MILP Solvers Under Limited Data AvailabilityCode1
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial OptimizationCode1
ASP: Learn a Universal Neural Solver!Code1
A Two-stage Reinforcement Learning-based Approach for Multi-entity Task AllocationCode1
Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial OptimizationCode1
CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial OptimizationCode1
Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement LearningCode1
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time WindowsCode1
Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural NetworksCode1
Combinatorial Optimization Perspective based Framework for Multi-behavior RecommendationCode1
An End-to-End Reinforcement Learning Approach for Job-Shop Scheduling Problems Based on Constraint ProgrammingCode1
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
Are Graph Neural Networks Optimal Approximation Algorithms?Code1
Combining Reinforcement Learning and Constraint Programming for Combinatorial OptimizationCode1
Adversarial Immunization for Certifiable Robustness on GraphsCode1
Active Learning Meets Optimized Item SelectionCode1
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