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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 501–550 of 1277 papers

TitleStatusHype
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
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
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
Temporal Sequencing of DocumentsCode0
Pointer Networks with Q-Learning for Combinatorial Optimization—0
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
High-Dimensional Prediction for Sequential Decision Making—0
Interferometric Neural NetworksCode0
Neural Packing: from Visual Sensing to Reinforcement Learning—0
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
GRASP: Accelerating Shortest Path Attacks via Graph Attention—0
Graph-SCP: Accelerating Set Cover Problems with Graph Neural NetworksCode0
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
GenCO: Generating Diverse Designs with Combinatorial Constraints—0
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
QAL-BP: An Augmented Lagrangian Quantum Approach for Bin PackingCode0
Enhancing Network Resilience through Machine Learning-powered Graph Combinatorial Optimization: Applications in Cyber Defense and Information Diffusion—0
Multi-Passive/Active-IRS Enhanced Wireless Coverage: Deployment Optimization and Cost-Performance Trade-off—0
Efficient LDPC Decoding using Physical Computation—0
Implementation of digital MemComputing using standard electronic componentsCode0
Constraints First: A New MDD-based Model to Generate Sentences Under Constraints—0
User Assignment and Resource Allocation for Hierarchical Federated Learning over Wireless Networks—0
Sub-universal variational circuits for combinatorial optimization problemsCode0
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement LearningCode0
Multitasking Evolutionary Algorithm Based on Adaptive Seed Transfer for Combinatorial Problem—0
Accelerating Exact Combinatorial Optimization via RL-based Initialization -- A Case Study in Scheduling—0
Accelerating Diffusion-based Combinatorial Optimization Solvers by Progressive Distillation—0
VN-Solver: Vision-based Neural Solver for Combinatorial Optimization over Graphs—0
Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs—0
Route Planning Using Nature-Inspired Algorithms—0
Accelerating Cutting-Plane Algorithms via Reinforcement Learning Surrogates—0
Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent—0
Learning to Select and Rank from Choice-Based Feedback: A Simple Nested Approach—0
FIS-ONE: Floor Identification System with One Label for Crowdsourced RF SignalsCode0
Transformers in Reinforcement Learning: A Survey—0
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