We describe an augmented intelligence system for simplifying and enhancing the modeling experience for operations research. Using this system, the user receives a suggested formulation of an optimization problem based on its description. To facilitate this process, we build an intuitive user interface system that enables the users to validate and edit the suggestions. We investigate controlled generation techniques to obtain an automatic suggestion of formulation. Then, we evaluate their effectiveness with a newly created dataset of linear programming problems drawn from various application domains.

翻译：我们描述一个扩大的情报系统,用于简化和加强业务研究的模型经验。使用这个系统,用户收到一个基于其描述的优化问题的建议。为了便利这一进程,我们建立了一个直观用户界面系统,使用户能够验证和编辑建议。我们调查受控生成技术,以获得自动拟订建议。然后,我们用新创建的从各种应用领域提取的线性编程问题数据集来评估其有效性。