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Previous issue (2021. Vol. 11, no. 4)

Modelling and Data Analysis

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 2219-3758

ISSN (online): 2311-9454

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

License: CC BY-NC 4.0

Published since 2011

Published 4 times a year

Free of fees
Open Access Journal

 

Application of the Johnson Problem to Solve Applied Problems 62

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Volkova T.B.
PhD in Physics and Matematics, Head of the Department of Mathematics and Cybernetics, Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russia
e-mail: tbvolkova@mail.ru

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

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.

Keywords: Johnson’s algorithm, integer programming

Column: Software

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

For Reference

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.
 
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