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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 1201–1250 of 1277 papers

TitleStatusHype
Exploiting Promising Sub-Sequences of Jobs to solve the No-Wait Flowshop Scheduling Problem—0
Exploring the Feature Space of TSP Instances Using Quality Diversity—0
Extended Deep Submodular Functions—0
Fair Disaster Containment via Graph-Cut Problems—0
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method—0
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization—0
Faster Matchings via Learned Duals—0
Faster quantum mixing for slowly evolving sequences of Markov chains—0
Faster width-dependent algorithm for mixed packing and covering LPs—0
Fast Hyperparameter Tuning for Ising Machines—0
Fast instance-specific algorithm configuration with graph neural network—0
Feature Selection for Classification with QAOA—0
Feature subset selection for Big Data via Chaotic Binary Differential Evolution under Apache Spark—0
Federated Combinatorial Multi-Agent Multi-Armed Bandits—0
Feeder Load Balancing using Neural Network—0
Fewer Truncations Improve Language Modeling—0
Finding and Exploring Promising Search Space for the 0-1 Multidimensional Knapsack Problem—0
Finding Support Examples for In-Context Learning—0
First-Order Bayesian Regret Analysis of Thompson Sampling—0
First-order regret bounds for combinatorial semi-bandits—0
Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search—0
Fixed Priority Global Scheduling from a Deep Learning Perspective—0
Focused Jump-and-Repair Constraint Handling for Fixed-Parameter Tractable Graph Problems Closed Under Induced Subgraphs—0
Forecasting high-dimensional dynamics exploiting suboptimal embeddings—0
Fragmentation trees reloaded—0
From Understanding Genetic Drift to a Smart-Restart Mechanism for Estimation-of-Distribution Algorithms—0
Fuzzy Integer Linear Programming Mathematical Models for Examination Timetable Problem—0
Gaze-Enabled Egocentric Video Summarization via Constrained Submodular Maximization—0
GenCO: Generating Diverse Designs with Combinatorial Constraints—0
Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization—0
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems—0
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness—0
Robust Bayesian Inference for Moving Horizon Estimation—0
Generalizing and Unifying Gray-box Combinatorial Optimization Operators—0
Generative Adversarial Training for Neural Combinatorial Optimization Models—0
Generative Neural Network based Spectrum Sharing using Linear Sum Assignment Problems—0
Generative Pre-Trained Transformer for Symbolic Regression Base In-Context Reinforcement Learning—0
Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolver—0
Generic CP-Supported CMSA for Binary Integer Linear Programs—0
Genetic Algorithm Based Combinatorial Optimization for the Optimal Design of Water Distribution Network of Gurudeniya Service Zone, Sri Lanka—0
Genetic Engineering Algorithm (GEA): An Efficient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems—0
GFPack++: Improving 2D Irregular Packing by Learning Gradient Field with Attention—0
GNCGCP - Graduated NonConvexity and Graduated Concavity Procedure—0
Graph2Seq: Scalable Learning Dynamics for Graphs—0
Graph Alignment for Benchmarking Graph Neural Networks and Learning Positional Encodings—0
Graph Learning for Combinatorial Optimization: A Survey of State-of-the-Art—0
Graph Learning: A Survey—0
Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm—0
Graph Minors Meet Machine Learning: the Power of Obstructions—0
Graph Neural Networks for Job Shop Scheduling Problems: A Survey—0
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