mlsanityData to 7 Oct 2026

A Survey of Optimization Modeling Meets LLMs: Progress and Future Directions

arXiv 2508.10047 ↗First posted 12 Aug 2025cs.AIcited by 30

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Abstract (arXiv)

By virtue of its great utility in solving real-world problems, optimization modeling has been widely employed for optimal decision-making across various sectors, but it requires substantial expertise from operations research professionals. With the advent of large language models (LLMs), new opportunities have emerged to automate the procedure of mathematical modeling. This survey presents a comprehensive and timely review of recent advancements that cover the entire technical stack, including data synthesis and fine-tuning for the base model, inference frameworks, benchmark datasets, and performance evaluation. In addition, we conducted an in-depth analysis on the quality of benchmark datasets, which was found to have a surprisingly high error rate. We cleaned the datasets and constructed a new leaderboard with fair performance evaluation in terms of base LLM model and datasets. We also build an online portal that integrates resources of cleaned datasets, code and paper repository to benefit the community. Finally, we identify limitations in current methodologies and outline future research opportunities.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 23 of its 40 references that are in the map. First posted on arXiv 12 Aug 2025.

Builds on

23 of 40 references.

References · 23

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  2. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  3. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  4. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  5. 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 873
  6. 2024To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningcited by 257
  7. 2024Scaling Large Language Model-based Multi-Agent Collaborationcited by 235
  8. 2023NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptionscited by 133
  9. 2024OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Modelscited by 105
  10. 2024LLMOPT: Learning to Define and Solve General Optimization Problems from Scratchcited by 102
  11. 2024OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modelingcited by 66
  12. 2023Large Language Models for Supply Chain Optimizationcited by 61
11 more
  1. 2024Autoformulation of Mathematical Optimization Models Using LLMscited by 48
  2. 2024Towards Foundation Models for Mixed Integer Linear Programmingcited by 30
  3. 2023Diagnosing Infeasible Optimization Problems Using Large Language Modelscited by 27
  4. 2024Solving General Natural-Language-Description Optimization Problems with Large Language Modelscited by 22
  5. 2024To the Globe (TTG): Towards Language-Driven Guaranteed Travel Planningcited by 21
  6. 2024Leveraging Large Language Models for Solving Rare MIP Challengescited by 10
  7. 2025Decision Information Meets Large Language Models: The Future of Explainable Operations Researchcited by 9
  8. 2024Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphscited by 7
  9. 2024City-LEO: Toward Transparent City Management Using LLM with End-to-End Optimizationcited by 5
  10. 2020Operational Research Literature as a Use Case for the Open Research Knowledge Graphcited by 1
  11. 2023LLM-based Frameworks for Power Engineering from Routine to Novel Taskscited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 5; 2026: 25.

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  1. 2025StepORLM: A Self-Evolving Framework With Generative Process Supervision For Operations Research Language Modelscited by 26
  2. 2026Constructing Industrial-Scale Optimization Modeling Benchmarkcited by 10
  3. 2025OptiMind: Teaching LLMs to Think Like Optimization Expertscited by 9
  4. 2025SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modelingcited by 8
  5. 2026Opt-Verifier: Unleashing the Power of LLMs for Optimization Modeling via Dual-Side Verificationcited by 5
  6. 2025Large Language Models in Operations Research: Methods, Applications, and Challengescited by 4
  7. 2026Strategy-Aware Optimization Modeling with Reasoning LLMscited by 4
  8. 2026From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modelingcited by 3
  9. 2025REG: A Regularization Optimizer for Robust Training Dynamicscited by 2
  10. 2026MIRROR: A Multi-Agent Framework with Iterative Adaptive Revision and Hierarchical Retrieval for Optimization Modeling in Operations Researchcited by 2
  11. 2026Execution-Verified Reinforcement Learning for Optimization Modelingcited by 2
  12. 2026TriVAL: A Tri-Validation Framework for Faithful Automatic Optimization Modelingcited by 2
18 more
  1. 2026Grammar-Aware Literate Generative Mathematical Programming with Compiler-in-the-Loopcited by 1
  2. 2026AutoOR: Scalably Post-training LLMs to Autoformulate Operations Research Problemscited by 1
  3. 2026Automated Reformulation of Robust Optimization via Memory-Augmented Large Language Modelscited by 1
  4. 2026MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resourcescited by 1
  5. 2026WildSplat: Feedforward Gaussian Splatting from Unposed In-the-Wild Imagescited by 1
  6. 2026PEARL: Solver-in-the-Loop Interactive Optimization Modeling from Natural Languagecited by 1
  7. 2026Co-evolving Agent Architectures and Interpretable Reasoning for Automated Optimizationcited by 0
  8. 2026Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimizationcited by 0
  9. 2026Generating Robust Portfolios of Optimization Models using Large Language Modelscited by 0
  10. 2026Large Language Models as Optimizers: A Survey of Direct vs. Tool-Augmented Approaches and Their Performance Frontierscited by 0
  11. 2026EvoOptiGraph: Weakness-Driven Coevolution via Graph-Based Structural Generation for Optimization Modelingcited by 0
  12. 2026IR2Solve: Structured Intermediate Representations for Cost-Efficient Optimization Autoformulationcited by 0
  13. 2026Admission Without Answers: Label-Free Certification and Experience Learning for LLM-Based Optimization Modelingcited by 0
  14. 2026SAILOR: Solver-Assisted Interactive LLM-based Optimization Recoverycited by 0
  15. 2026Relative Generalization Invariance of LLM Pretrainingcited by 0
  16. 2026Learning to Optimize through Solver-Grounded Self-Playcited by 0
  17. 2026TACIT: Optimization Models that Learn from Their Mistakescited by 0
  18. 2026Right Answers, Costly Models: The Efficiency Gap in LLM-based Optimization Modelingcited by 0