Beyond QAOA: A Review of AI and Quantum Computing for Adaptive Combinatorial Optimization
quant-ph, cs.LG, math.OC
Submitted: 2026-10-08
Updated: 2026-10-08
Terminology
Sources
- A Quantum Approximate Optimization Algorithm
- Approximate Solutions of Combinatorial Problems via Quantum Relaxations
- Reinforcement Learning for Variational Quantum Circuits Design
- GNN-Guided Graph Coarsening and Adaptive QUBO Penalties for the Capacitated Vehicle Routing Problem with Time Windows on a Quantum Annealer
- CVaR-Assisted Custom Penalty Function for Constrained Optimization
- Qubit-Scalable CVRP via Lagrangian Knapsack Decomposition and Noise-Aware Quantum Execution
- Parametrized quantum policies for reinforcement learning
- Vehicle Routing Problems via Quantum Graph Attention Network Deep Reinforcement Learning
- A hybrid quantum-classical neural network for learning to route
- Quantum End-to-End Learning for Contextual Combinatorial Optimization
- Diagnosing Simulation and Hardware Barriers to Cross-Size Transfer in Equivariant Quantum Reinforcement Learning
- Neural QAOA$^{2}$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization
- Hybrid Learning and Optimization methods for solving Capacitated Vehicle Routing Problem
- RL-Guided Quantum-ALNS for Constrained VRP
- The QuaST Decision Tree: Achieving Automation With Data-Based Recommendations
- Adaptive Shot Allocation for Recursive QAOA via Reinforcement Learning
- AutoQResearch: LLM-Guided Closed-Loop Policy Search for Adaptive Variational Quantum Optimization
- DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems
- Compositional Quantum Heuristics for Max-Clique Detection
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