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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

Showing 201225 of 1277 papers

TitleStatusHype
Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation0
Systematic and Efficient Construction of Quadratic Unconstrained Binary Optimization Forms for High-order and Dense Interactions0
HyColor: An Efficient Heuristic Algorithm for Graph Coloring0
Domain Switching on the Pareto Front: Multi-Objective Deep Kernel Learning in Automated Piezoresponse Force Microscopy0
Adam assisted Fully informed Particle Swarm Optimzation ( Adam-FIPSO ) based Parameter Prediction for the Quantum Approximate Optimization Algorithm (QAOA)0
Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLMCode0
Latent Guided Sampling for Combinatorial OptimizationCode0
EALG: Evolutionary Adversarial Generation of Language Model-Guided Generators for Combinatorial Optimization0
Solving the Pod Repositioning Problem with Deep Reinforced Adaptive Large Neighborhood Search0
Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization0
Learning Distributions over Permutations and Rankings with Factorized Representations0
Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees0
LLM-ODDR: A Large Language Model Framework for Joint Order Dispatching and Driver Repositioning0
Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization0
Learning for Dynamic Combinatorial Optimization without Training Data0
RedAHD: Reduction-Based End-to-End Automatic Heuristic Design with Large Language Models0
Efficient Optimization Accelerator Framework for Multistate Ising Problems0
Demand Selection for VRP with Emission QuotaCode0
MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search0
LMask: Learn to Solve Constrained Routing Problems with Lazy Masking0
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial OptimizationCode0
Tropical Attention: Neural Algorithmic Reasoning for Combinatorial Algorithms0
STRCMP: Integrating Graph Structural Priors with Language Models for Combinatorial Optimization0
Neural Quantum Digital Twins for Optimizing Quantum Annealing0
A Quantum-Enhanced Power Flow and Optimal Power Flow based on Combinatorial Reformulation0
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