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Combinatorial Optimization
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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.
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Large Language Models for Combinatorial Optimization: A Systematic Review
Higher-Order Neuromorphic Ising Machines -- Autoencoders and Fowler-Nordheim Annealers are all you need for Scalability
On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis
HeurAgenix: Leveraging LLMs for Solving Complex Combinatorial Optimization Challenges
GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models
Synthesizing Min-Max Control Barrier Functions For Switched Affine Systems
Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization
Large Language Models for Design Structure Matrix Optimization
Systematic and Efficient Construction of Quadratic Unconstrained Binary Optimization Forms for High-order and Dense Interactions
Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation
Solving the Job Shop Scheduling Problem with Graph Neural Networks: A Customizable Reinforcement Learning Environment
HyColor: An Efficient Heuristic Algorithm for Graph Coloring
HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial Optimization
Domain Switching on the Pareto Front: Multi-Objective Deep Kernel Learning in Automated Piezoresponse Force Microscopy
Adam assisted Fully informed Particle Swarm Optimzation ( Adam-FIPSO ) based Parameter Prediction for the Quantum Approximate Optimization Algorithm (QAOA)
Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM
Latent Guided Sampling for Combinatorial Optimization
EALG: Evolutionary Adversarial Generation of Language Model-Guided Generators for Combinatorial Optimization
Solving the Pod Repositioning Problem with Deep Reinforced Adaptive Large Neighborhood Search
Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization
Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees
Learning Distributions over Permutations and Rankings with Factorized Representations
LLM-ODDR: A Large Language Model Framework for Joint Order Dispatching and Driver Repositioning
Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization
Learning for Dynamic Combinatorial Optimization without Training Data
RedAHD: Reduction-Based End-to-End Automatic Heuristic Design with Large Language Models
Efficient Optimization Accelerator Framework for Multistate Ising Problems
Structured Reinforcement Learning for Combinatorial Decision-Making
MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search
Demand Selection for VRP with Emission Quota
LMask: Learn to Solve Constrained Routing Problems with Lazy Masking
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial Optimization
Tropical Attention: Neural Algorithmic Reasoning for Combinatorial Algorithms
STRCMP: Integrating Graph Structural Priors with Language Models for Combinatorial Optimization
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