Usynin Andrey Vyacheslavovich, Student, Department of Big Data Analytics and Video Analysis Methods, Ural Federal University named after the first President of Russia B.N. Yeltsin
Mashanov Ilya Vladimirovich, Student, Department of Big Data Analytics and Video Analysis Methods, Ural Federal University named after the first President of Russia B.N. Yeltsin
Dudarev Dmitriy Konstantinovich, Student, Department of Big Data Analytics and Video Analysis Methods, Ural Federal University named after the first President of Russia B.N. Yeltsin
Medvedev Maksim Aleksandrovich, Associate Professor, Department of Big Data Analytics and Video Analysis Methods, Ural Federal University named after the first President of Russia B.N. Yeltsin
Abstract
This paper presents a tool for automating the construction of production planning systems, which is designed to convert the conditions of mathematical programming problems described in the Univer table framework into executable Python code using the PuLP library. The implementation of this tool solves the actual problem associated with the need to manually transfer models developed by analysts into industrial code, which often leads to lost time, inaccuracies and increased development costs. The proposed solution provides an automated and error-free transition from analytical prototypes to production implementation, reducing implementation time and increasing the efficiency of development teams and analysts. As a result of automation, development costs are reduced, the probability of errors is reduced, and the cycle of implementation of mathematical optimization models into production practice is significantly accelerated.
KEYWORDS: Python, PuLP, Excel, Univer, TypeScript, code generation, mathematical programming, linear programming, digitalization of manufacturing, automation.
Download article COMPUTER TOOL FOR AUTOMATION OF DESIGNING OF PRODUCTION PLANNING SYSTEMS
