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Modelling and Data Analysis
2021. Vol. 11, no. 4, 49–58
https://doi.org/10.17759/mda.2021110404
ISSN: 2219-3758 / 2311-9454 (online)

Application of the Johnson Problem to Solve Applied Problems

 
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Abstract

This article discusses the application of Johnson’s algorithm to analyze the work of a volunteer help desk and the work of an online store if the initial data for the algorithm are random numbers from a given interval. For this purpose, a program has been developed for solving the Johnson problem for modeling work, i.e. simulating the processing of applications (orders, calls), written in the Python programming language using IDE – PyCharm 2021.1, Qt Designer and PyQt5, in which the processing time of applications is a random variable from a given interval. The analysis of the results obtained allows us to make recommendations on the number of applications that the service system can process if the processing time is random, but belongs to a given interval, as well as predict the waiting time for applications to arrive.

General Information

Keywords: Johnson’s algorithm, integer programming

Journal rubric: Software

OpenAlex citations: 0

OpenAlex trends: Engineering Education and Technology

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Number of citations: 0

Topics

Engineering Education and Technology

This cluster of papers explores the concept of Smart University within the context of Digital Ecosystems, focusing on topics such as Internet of Things, Artificial Intelligence, cognitive modeling, educational technology, innovation management, predictive maintenance, knowledge management, and industrial control systems. The papers discuss the principles and semantics of digital ecosystems, machine learning algorithms for smart data analysis, ontology of smart classrooms, mobile social networking for smart campuses, and the development and evaluation models for smart universities.

Number of works: 12917  |  Total number of citations: 36014

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DOI: https://doi.org/10.17759/mda.2021110404

Published

For citation: Volkova, T.B., Osokina, A.D. (2021). Application of the Johnson Problem to Solve Applied Problems. Modelling and Data Analysis, 11(4), 49–58. (In Russ.). https://doi.org/10.17759/mda.2021110404

© Volkova T.B., Osokina A.D., 2021

License: CC BY-NC 4.0

References

  1. A. Korbut and Yu. Yu. Finkelstein “Discrete programming” Moscow: Nauka, 1969.
  2. Kofman “Introduction to applied combinatorics” Moscow: Nauka, 1975.
  3. Kormen, C. Leiserson, R. Rivest “Algorithms: construction and analysis 2nd ed.” Moscow: “Williams”, 2007.
  4. M. Johnson. Optimal two – and three-stage production schedules with setup times included. P-402. Santa Monica, California, the RAND Corporation, 1953. – P. 10.

Information About the Authors

Tatiana B. Volkova, Candidate of Science (Physics and Matematics), Associate Professor, Head of the Department of Mathematics and Cybernetics, Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russian Federation, e-mail: tbvolkova@mail.ru

Anastasia D. Osokina, Student of the Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0003-1576-177X, e-mail: nastaosokina2@gmail.com

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