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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 151–200 of 1277 papers

TitleStatusHype
LIAR: Leveraging Alignment (Best-of-N) to Jailbreak LLMs in Seconds—0
CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention—0
Scalable iterative pruning of large language and vision models using block coordinate descent—0
Approximation Algorithms for Combinatorial Optimization with PredictionsCode0
Large Language Models for Combinatorial Optimization of Design Structure Matrix—0
Design And Optimization Of Multi-rendezvous Manoeuvres Based On Reinforcement Learning And Convex Optimization—0
Beyond the Heatmap: A Rigorous Evaluation of Component Impact in MCTS-Based TSP SolversCode1
Liner Shipping Network Design with Reinforcement Learning—0
Neuro-Symbolic Rule Lists—0
MBL-CPDP: A Multi-objective Bilevel Method for Cross-Project Defect Prediction via Automated Machine Learning—0
Learn to Solve Vehicle Routing Problems ASAP: A Neural Optimization Approach for Time-Constrained Vehicle Routing Problems with Finite Vehicle Fleet—0
Assessing and Enhancing Graph Neural Networks for Combinatorial Optimization: Novel Approaches and Application in Maximum Independent Set Problems—0
A Random-Key Optimizer for Combinatorial Optimization—0
Neural Networks and (Virtual) Extended Formulations—0
Deep memetic models for combinatorial optimization problems: application to the tool switching problem—0
Towards Geometry-Preserving Reductions Between Constraint Satisfaction Problems (and other problems in NP)—0
Multi-IRS Enhanced Wireless Coverage: Deployment Optimization Based on Large-Scale Channel Knowledge—0
Theoretically Grounded Pruning of Large Ground Sets for Constrained, Discrete Optimization—0
Permutation Picture of Graph Combinatorial Optimization Problems—0
Offline reinforcement learning for job-shop scheduling problems—0
Enhancing In-vehicle Multiple Object Tracking Systems with Embeddable Ising Machines—0
Selection of Filters for Photonic Crystal Spectrometer Using Domain-Aware Evolutionary Algorithms—0
LLMOPT: Learning to Define and Solve General Optimization Problems from ScratchCode2
Initialization Method for Factorization Machine Based on Low-Rank Approximation for Constructing a Corrected Approximate Ising Model—0
Unsupervised Training of Diffusion Models for Feasible Solution Generation in Neural Combinatorial Optimization—0
Neural Solver Selection for Combinatorial OptimizationCode0
Combinatorial optimization of the coefficient of determinationCode0
D-Wave's Nonlinear-Program Hybrid Solver: Description and Performance Analysis—0
WardropNet: Traffic Flow Predictions via Equilibrium-Augmented LearningCode0
Balancing Pareto Front exploration of Non-dominated Tournament Genetic Algorithm (B-NTGA) in solving multi-objective NP-hard problems with constraints—0
Synthesizing Interpretable Control Policies through Large Language Model Guided SearchCode0
Rethinking Selection in Generational Genetic Algorithms to Solve Combinatorial Optimization Problems: An Upper Bound-based Parent Selection Strategy for Recombination—0
CreDes: Causal Reasoning Enhancement and Dual-End Searching for Solving Long-Range Reasoning Problems using LLMs—0
Towards Fairness and Privacy: A Novel Data Pre-processing Optimization Framework for Non-binary Protected AttributesCode1
MG-Net: Learn to Customize QAOA with Circuit Depth AwarenessCode0
A 2-approximation algorithm for the softwired parsimony problem on binary, tree-child phylogenetic networks—0
Multi-objective Evolution of Heuristic Using Large Language Model—0
Quantum evolutionary algorithm for TSP combinatorial optimisation problem—0
Extended Deep Submodular Functions—0
Offline Reinforcement Learning for Learning to Dispatch for Job Shop SchedulingCode0
Machine Learning and Constraint Programming for Efficient Healthcare Scheduling—0
Diversity-Driven View Subset Selection for Indoor Novel View SynthesisCode0
Deep Generative Model for Mechanical System Configuration Design—0
Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural NetworksCode1
Parallel AutoRegressive Models for Multi-Agent Combinatorial OptimizationCode1
Large-scale Urban Facility Location Selection with Knowledge-informed Reinforcement Learning—0
DataSculpt: Crafting Data Landscapes for Long-Context LLMs through Multi-Objective PartitioningCode1
Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based SamplingCode0
A GREAT Architecture for Edge-Based Graph Problems Like TSPCode0
Bridging Large Language Models and Optimization: A Unified Framework for Text-attributed Combinatorial Optimization—0
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