Generalizable Heuristic Generation Through LLMs with Meta-Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Shi, Yiding, Zhou, Jianan, Song, Wen, Bi, Jieyi, Wu, Yaoxin, Cao, Zhiguang, Zhang, Jie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty
by: Lin, Tianjue, et al.
Published: (2026)
by: Lin, Tianjue, et al.
Published: (2026)
Learning to Handle Complex Constraints for Vehicle Routing Problems
by: Bi, Jieyi, et al.
Published: (2024)
by: Bi, Jieyi, et al.
Published: (2024)
Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
by: Bi, Jieyi, et al.
Published: (2026)
by: Bi, Jieyi, et al.
Published: (2026)
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
by: Zhang, Cong, et al.
Published: (2022)
by: Zhang, Cong, et al.
Published: (2022)
Collaboration! Towards Robust Neural Methods for Routing Problems
by: Zhou, Jianan, et al.
Published: (2024)
by: Zhou, Jianan, et al.
Published: (2024)
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
by: Zhou, Jianan, et al.
Published: (2024)
by: Zhou, Jianan, et al.
Published: (2024)
Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
by: Zhang, Cong, et al.
Published: (2024)
by: Zhang, Cong, et al.
Published: (2024)
Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
by: Li, Qi, et al.
Published: (2025)
by: Li, Qi, et al.
Published: (2025)
Rethinking Light Decoder-based Solvers for Vehicle Routing Problems
by: Huang, Ziwei, et al.
Published: (2025)
by: Huang, Ziwei, et al.
Published: (2025)
Learning Memory-Enhanced Improvement Heuristics for Flexible Job Shop Scheduling
by: Wang, Jiaqi, et al.
Published: (2026)
by: Wang, Jiaqi, et al.
Published: (2026)
Enhancing Cross-Problem Vehicle Routing via Federated Learning
by: Meng, Xiangchi, et al.
Published: (2026)
by: Meng, Xiangchi, et al.
Published: (2026)
RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States
by: Xiao, Xiangjie, et al.
Published: (2026)
by: Xiao, Xiangjie, et al.
Published: (2026)
Adversarial Instance Generation and Robust Training for Neural Combinatorial Optimization with Multiple Objectives
by: Liu, Wei, et al.
Published: (2026)
by: Liu, Wei, et al.
Published: (2026)
Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineering
by: Wang, Chen, et al.
Published: (2025)
by: Wang, Chen, et al.
Published: (2025)
Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation
by: Zhu, Jianghan, et al.
Published: (2025)
by: Zhu, Jianghan, et al.
Published: (2025)
Probing Neural Combinatorial Optimization Models
by: Zhang, Zhiqin, et al.
Published: (2025)
by: Zhang, Zhiqin, et al.
Published: (2025)
DARA: Few-shot Budget Allocation in Online Advertising via In-Context Decision Making with RL-Finetuned LLMs
by: Song, Mingxuan, et al.
Published: (2026)
by: Song, Mingxuan, et al.
Published: (2026)
Partial Column Generation with Graph Neural Networks for Team Formation and Routing
by: Dall'Olio, Giacomo, et al.
Published: (2025)
by: Dall'Olio, Giacomo, et al.
Published: (2025)
Adversarial Generative Flow Network for Solving Vehicle Routing Problems
by: Zhang, Ni, et al.
Published: (2025)
by: Zhang, Ni, et al.
Published: (2025)
Graph Neural Networks for Job Shop Scheduling Problems: A Survey
by: Smit, Igor G., et al.
Published: (2024)
by: Smit, Igor G., et al.
Published: (2024)
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
by: Berto, Federico, et al.
Published: (2023)
by: Berto, Federico, et al.
Published: (2023)
VAGPO: Vision-augmented Asymmetric Group Preference Optimization for Graph Routing Problems
by: Liu, Shiyan, et al.
Published: (2025)
by: Liu, Shiyan, et al.
Published: (2025)
Automated Reinforcement Learning: An Overview
by: Afshar, Reza Refaei, et al.
Published: (2022)
by: Afshar, Reza Refaei, et al.
Published: (2022)
DONOD: Efficient and Generalizable Instruction Fine-Tuning for LLMs via Model-Intrinsic Dataset Pruning
by: Hu, Jucheng, et al.
Published: (2025)
by: Hu, Jucheng, et al.
Published: (2025)
Calibration-Aware Policy Optimization for Reasoning LLMs
by: Wang, Ziqi, et al.
Published: (2026)
by: Wang, Ziqi, et al.
Published: (2026)
Avoiding $\mathbf{exp(R_{max})}$ scaling in RLHF through Preference-based Exploration
by: Chen, Mingyu, et al.
Published: (2025)
by: Chen, Mingyu, et al.
Published: (2025)
Schema-Adaptive Tabular Representation Learning with LLMs for Generalizable Multimodal Clinical Reasoning
by: Mao, Hongxi, et al.
Published: (2026)
by: Mao, Hongxi, et al.
Published: (2026)
It Takes a Good Model to Train a Good Model: Generalized Gaussian Priors for Optimized LLMs
by: Wu, Jun, et al.
Published: (2025)
by: Wu, Jun, et al.
Published: (2025)
Learning with Foresight: Enhancing Neural Routing Policy via Multi-Node Lookahead Prediction
by: Jiang, Xia, et al.
Published: (2026)
by: Jiang, Xia, et al.
Published: (2026)
DRAGON: LLM-Driven Decomposition and Reconstruction Agents for Large-Scale Combinatorial Optimization
by: Chen, Shengkai, et al.
Published: (2026)
by: Chen, Shengkai, et al.
Published: (2026)
Large Language Models as End-to-end Combinatorial Optimization Solvers
by: Jiang, Xia, et al.
Published: (2025)
by: Jiang, Xia, et al.
Published: (2025)
MViewRouter: Internalizing Geometric Equivariance via Multi-view Alternating Attention for Combinatorial Routing
by: Liu, Shiyan, et al.
Published: (2026)
by: Liu, Shiyan, et al.
Published: (2026)
RRNCO: Towards Real-World Routing with Neural Combinatorial Optimization
by: Son, Jiwoo, et al.
Published: (2025)
by: Son, Jiwoo, et al.
Published: (2025)
RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
by: Yi, Hang, et al.
Published: (2026)
by: Yi, Hang, et al.
Published: (2026)
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems
by: Smit, Igor G., et al.
Published: (2024)
by: Smit, Igor G., et al.
Published: (2024)
MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design
by: Yan, Zimo, et al.
Published: (2025)
by: Yan, Zimo, et al.
Published: (2025)
SA-EMO: Structure-Aligned Encoder Mixture of Operators for Generalizable Full-waveform Inversion
by: Zhenyu, Wang, et al.
Published: (2025)
by: Zhenyu, Wang, et al.
Published: (2025)
MeshONet: A Generalizable and Efficient Operator Learning Method for Structured Mesh Generation
by: Xiao, Jing, et al.
Published: (2025)
by: Xiao, Jing, et al.
Published: (2025)
Rational Synthesizers or Heuristic Followers? Analyzing LLMs in RAG-based Question-Answering
by: Naphade, Atharv
Published: (2026)
by: Naphade, Atharv
Published: (2026)
Light-IF: Endowing LLMs with Generalizable Reasoning via Preview and Self-Checking for Complex Instruction Following
by: Wang, Chenyang, et al.
Published: (2025)
by: Wang, Chenyang, et al.
Published: (2025)
Similar Items
-
Learning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty
by: Lin, Tianjue, et al.
Published: (2026) -
Learning to Handle Complex Constraints for Vehicle Routing Problems
by: Bi, Jieyi, et al.
Published: (2024) -
Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
by: Bi, Jieyi, et al.
Published: (2026) -
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
by: Zhang, Cong, et al.
Published: (2022) -
Collaboration! Towards Robust Neural Methods for Routing Problems
by: Zhou, Jianan, et al.
Published: (2024)