mlsanityData to 14 Oct 2026

ORPilot: A Production-Oriented Agentic LLM-for-OR Tool for Optimization Modeling

arXiv 2605.02728 ↗First posted 4 May 2026cs.AIcited by 2

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

This paper presents ORPilot, an open-source agentic AI system that translates real-world business problems into solver-ready optimization models. Unlike academic LLM-for-OR tools that assume clean problem specifications with preformatted inline data, ORPilot is designed for production conditions: ambiguous descriptions, large-scale raw operational data, and the need for portability across solver backends. The system introduces four novel components: (1) a conversational interview agent to elicit complete problem specifications, (2) a data collection agent that retrieves data independently of prompts, (3) a parameter computation agent to bridge raw tabular data and model-ready parameters, and (4) a solver-agnostic Intermediate Representation (IR) for deterministic, zero-LLM-call recompilation to Gurobi, CPLEX, PuLP, Pyomo, or OR-Tools solvers. Additionally, self-correcting retry loops utilize solver tracebacks for targeted repairs. ORPilot represents the first attempt to target production-level business problems rather than textbook operations research (OR) cases. Evaluation on real-world problems demonstrates promising results. When tested against traditional academic benchmarks: IndustryOR, NL4OPT and NLP4LP, ORPilot outperformed state-of-the-art tools in accuracy on the IndustryOR benchmark and delivered comparable performance on NL4OPT and NLP4LP.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 17 of its 19 references that are in the map. First posted on arXiv 4 May 2026.

Builds on

17 of 19 references.

Closest ancestors · 1

Same direction, newest first

  1. 2025OR-LLM-Agent: Automating Modeling and Solving of Operations Research Optimization Problems with Reasoning LLM13 Mar

Other references · 16

  1. 2023NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptionscited by 135
  2. 2024ORLM: A Customizable Framework in Training Large Models for Automated Optimization Modelingcited by 124
  3. 2024OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Modelscited by 109
  4. 2024LLMOPT: Learning to Define and Solve General Optimization Problems from Scratchcited by 102
  5. 2023Large Language Models for Supply Chain Optimizationcited by 64
  6. 2025OptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modelingcited by 49
  7. 2024Autoformulation of Mathematical Optimization Models Using LLMscited by 48
  8. 2024LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generationcited by 45
  9. 2023OptiMUS: Optimization Modeling Using MIP Solvers and large language modelscited by 39
  10. 2024OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scalecited by 38
  11. 2024Solving General Natural-Language-Description Optimization Problems with Large Language Modelscited by 22
  12. 2024From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifestocited by 11
4 more
  1. 2025EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulationscited by 9
  2. 2025Large Language Models in Operations Research: Methods, Applications, and Challengescited by 6
  3. 2024Abstract Operations Research Modeling Using Natural Language Inputscited by 4
  4. 2025Automatic MILP Model Construction for Multi-Robot Task Allocation and Scheduling Based on Large Language Modelscited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026YUKTI: From Natural-Language Situations to Robust, Verifiable Decisions An Uncertainty-Typed Proposition IR, Assumption-Robust Pareto Frontiers, and a Regret Certificatecited by 0
  2. 2026Ask Before You Optimize: Dynamic Pre-Formulation Clarification for Interactive Optimizationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Agentic AI-Assisted Modeling for Production Scheduling: Assessment in Constraint Programming
  2. 2026OR-Space: A Full-Lifecycle Workspace Benchmark for Industrial Optimization Agents
  3. 2026Opti-Agent-Bench: Benchmarking End-to-End Optimization R&D Agents on Real-World Business Problems
  4. 2025ORMind: A Cognitive-Inspired End-to-End Reasoning Framework for Operations Research
  5. 2025Ask, Clarify, Optimize: Human-LLM Agent Collaboration for Smarter Inventory Control
  6. 2026MIRROR: A Multi-Agent Framework with Iterative Adaptive Revision and Hierarchical Retrieval for Optimization Modeling in Operations Research
  7. 2026Let's Have a Conversation: Designing and Evaluating LLM Agents for Interactive Optimization
  8. 2026OptiSkill: A Hierarchical and Evolving SkillBank for LLM-Based Optimization Modeling