# Cardinal Optimizer (COPT) User Guide

arXiv: https://arxiv.org/abs/2208.14314 · HTML: https://mlsanity.com/paper/2208.14314/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Aug 2022.

## Built on by (most cited first, 16 of 16)

- [Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling](https://mlsanity.com/paper/2505.11792/) (2025)
- [OR-LLM-Agent: Automating Modeling and Solving of Operations Research Optimization Problems with Reasoning LLM](https://mlsanity.com/paper/2503.10009/) (2025)
- [Leveraging Large Language Models for Solving Rare MIP Challenges](https://mlsanity.com/paper/2409.04464/) (2024)
- [Decision Information Meets Large Language Models: The Future of Explainable Operations Research](https://mlsanity.com/paper/2502.09994/) (2025)
- [SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling](https://mlsanity.com/paper/2510.05115/) (2025)
- [MPAX: Mathematical Programming in JAX](https://mlsanity.com/paper/2412.09734/) (2024)
- [OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling](https://mlsanity.com/paper/2601.19924/) (2026)
- [Disciplined Biconvex Programming](https://mlsanity.com/paper/2511.01813/) (2025)
- [MIRROR: A Multi-Agent Framework with Iterative Adaptive Revision and Hierarchical Retrieval for Optimization Modeling in Operations Research](https://mlsanity.com/paper/2602.03318/) (2026)
- [Execution-Verified Reinforcement Learning for Optimization Modeling](https://mlsanity.com/paper/2604.00442/) (2026)
- [Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching](https://mlsanity.com/paper/2305.12352/) (2023)
- [MILP-Evo: Closed-Loop Fully Automatic Design of MILP Solvers](https://mlsanity.com/paper/2607.18252/) (2026)
- [Enhancing Delta Compression in LLMs via SVD-based Quantization Error Minimization](https://mlsanity.com/paper/2506.11087/) (2025)
- [Step-Opt: Boosting Optimization Modeling in LLMs through Iterative Data Synthesis and Structured Validation](https://mlsanity.com/paper/2506.17637/) (2025)
- [Disciplined Bilevel Programming](https://mlsanity.com/paper/2609.00644/) (2026)
- [Beyond Verified Answers: Solver-Informed Self-Distillation for Bootstrapping Operations Research Language Models](https://mlsanity.com/paper/2609.09957/) (2026)

## Abstract (arXiv)

Cardinal Optimizer is a high-performance mathematical programming solver for efficiently solving largescale optimization problem. This documentation provides basic introduction to the Cardinal Optimizer.