DOI: https://doi.org/10.15587/1729-4061.2019.157201

A method to form control over queuing systems taking into consideration the probabilistic character of demand

Igor Lutsenko, Illia Dmytriiev, Nina Avanesova, Iryna Semenyshyna, Zhanna Rozhnenko, Oleg Danileyko

Abstract


Queueing systems (QS) belong to the class of systems the quality of control over which cannot be assessed in real time. In other words, it is impossible to apply methods of classic search optimization at the stage of control design.

The current practice of control design implies the acquisition of historical data required to model an operational process in order to choose its best control parameters. These parameters include: determining the size of the planning horizon, forecasting interval, the type of a forecasting model. All these parameters represent the degrees of freedom of search optimization. Upon defining these parameters, modeling process is repeated for different values of shift in the demand forecasted value towards the region of large positive values. Such a shift leads to an increase in the QS inventory levels and a decrease in the likelihood of a product deficit occurrence.

Process efficiency is compromised by both the insurance stocks and a shortage of products. However, experience has shown that a certain shift in control towards an increase in the inventory levels improves the efficiency of their functioning.

Thus, the task on QS inventory control implies the substantiation of choice of control parameters in the process of cyclic simulation of the operational process based on the set of historical data.

Despite the long history of the subject, there is no method at present whose application would make it possible to obtain control, the parameters of which could be considered justified. This relates to that the best control parameters are determined not by examining the quality of economic models of an operational process but rather by studying the quality of quantitative models of this process.

In order to further advance the theory and methods of control, we have constructed an economic-mathematical model of uncoordinated operation. The model proposed takes into consideration the result of interaction between processes in the buffering channel and processes in the client channel that aims to meet customer demand considering a factor of information impact from marketing technologies on the internal and external consumer.

The structure of the constructed mathematical model has passed the validation procedure for consistency, in the process of comparing the redundant and deficient operations.

A procedure for estimation optimization of the simulated process has showed a possibility to determine the optimal control parameters based on the criterion for a maximum criterion of efficiency of operational process

Keywords


optimal control; demand forecasting; prediction; insurance stock; effectiveness formula

References


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Sevastianov, L. A., Vasilyev, S. A. (2017). Large-scale queuing systems and services pricing. 2017 9th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). doi: https://doi.org/10.1109/icumt.2017.8255186

Bahareh, A., Nadia, B. (2014). Determining supply chain safety stock level and location. Journal of Industrial Engineering and Management, 10 (1), 42–71. doi: https://doi.org/10.3926/jiem.543

Lutsenko, I. (2016). Definition of efficiency indicator and study of its main function as an optimization criterion. Eastern-European Journal of Enterprise Technologies, 6 (2 (84)), 24–32. doi: https://doi.org/10.15587/1729-4061.2016.85453

Lutsenko, I. (2015). Identification of target system operations. Development of global efficiency criterion of target operations. Eastern-European Journal of Enterprise Technologies, 2 (2 (74)), 35–40. doi: https://doi.org/10.15587/1729-4061.2015.38963

Lutsenko, I., Vihrova, E., Fomovskaya, E., Serdiuk, O. (2016). Development of the method for testing of efficiency criterion of models of simple target operations. Eastern-European Journal of Enterprise Technologies, 2 (4 (80)), 42–50. doi: https://doi.org/10.15587/1729-4061.2016.66307

Lutsenko, I., Fomovskaya, E., Oksanych, I., Vikhrova, E., Serdiuk, O. (2017). Formal signs determination of efficiency assessment indicators for the operation with the distributed parameters. Eastern-European Journal of Enterprise Technologies, 1 (4 (85)), 24–30. doi: https://doi.org/10.15587/1729-4061.2017.91025

Lutsenko, I., Fomovskaya, E., Oksanych, I., Koval, S., Serdiuk, O. (2017). Development of a verification method of estimated indicators for their use as an optimization criterion. Eastern-European Journal of Enterprise Technologies, 2 (4 (86)), 17–23. doi: https://doi.org/10.15587/1729-4061.2017.95914

Lutsenko, I., Fomovskaya, O., Vihrova, E., Serdiuk, O., Fomovsky, F. (2018). Development of test operations with different duration in order to improve verification quality of effectiveness formula. Eastern-European Journal of Enterprise Technologies, 1 (4 (91)), 42–49. doi: https://doi.org/10.15587/1729-4061.2018.121810

Lutsenko, I., Oksanych, I., Shevchenko, I., Karabut, N. (2018). Development of the method for modeling operational processes for tasks related to decision making. Eastern-European Journal of Enterprise Technologies, 2 (4 (92)), 26–32. doi: https://doi.org/10.15587/1729-4061.2018.126446

Lutsenko, I., Fomovskaya, O., Konokh, I., Oksanych, I. (2017). Development of a method for the accelerated two-stage search for an optimal control trajectory in periodical processes. Eastern-European Journal of Enterprise Technologies, 3 (2 (87)), 47–55. doi: https://doi.org/10.15587/1729-4061.2017.103731


GOST Style Citations


Executive leadership course. Englewood Cliffs, 1963. 808 p.

Gavrilov D. A. Upravlenie proizvodstvom na baze standarta MRP II. Sankt-Peterburg: Piter, 2002. 320 p.

Drucker P. F. Management: Tasks, Responsibilities, Practices. Harper Collins, 2009. 864 p.

Zaycev Yu. P. Issledovanie operaciy. Moscow: Vysshaya shkola, 1975. 320 p.

Lutsenko I. Optimal control of systems engineering. development of a general structure of the technological conversion subsystem (Part 2) // Eastern-European Journal of Enterprise Technologies. 2015. Vol. 1, Issue 2 (73). P. 43–50. doi: https://doi.org/10.15587/1729-4061.2015.36246 

Ekonomiko-matematicheskie metody i prikladnye modeli / Fedoseev V. V., Garmash A. N., Dayitbegov D. M., Orlova I. V., Polovnikov V. A. Moscow: YUNITI, 1999. 391 p.

Boulaksil Y. Safety stock placement in supply chains with demand forecast updates // Operations Research Perspectives. 2016. Vol. 3. P. 27–31. doi: https://doi.org/10.1016/j.orp.2016.07.001 

Ilyina T. A. Determining the optimal level of inventory of material and technical resources in an industrial plant // Vestnik Samarskogo gosudarstvennogo tekhnicheskogo universiteta. Seriya: Ekonomicheskie nauki. 2013. Issue 1. P. 59–66.

Skochinskaya V. A. Methods for calculation of reserve stock volume taking into account significance of material resources // Vestnik BNTU. 2007. Issue 5. P. 52–57.

Kölling A. Asymmetries in labor demand: Do loss aversion and endowment effects affect labor demand elasticities on the establishment level? // The Journal of Economic Asymmetries. 2018. Vol. 18. P. e00098. doi: https://doi.org/10.1016/j.jeca.2018.e00098 

Atamanchuk Yu. S., Pasenchenko Yu. A. Modeling of enterprise's inventory management with allowance for uncertain demand // Aktualni problemy ekonomiky ta upravlinnia. 2016. Issue 10. URL: http://ela.kpi.ua/jspui/handle/123456789/22508

Hubrich K., Skudelny F. Forecast Combination for Euro Area Inflation – A Cure in Times of Crisis? // Finance and Economics Discussion Series. 2016. Vol. 2016, Issue 104. doi: https://doi.org/10.17016/feds.2016.104 

Lee T. H., Adams G. E., Gaines W. M. Computer process control: Modeling and Optimization. Wiley, 1968. 386 p.

Wu H. The lean manufacture research in environment of the supply chain of modern industry engineering // 2009 16th International Conference on Industrial Engineering and Engineering Management. 2009. doi: https://doi.org/10.1109/icieem.2009.5344586 

Green C. G., Martin R. D. Robust Detection of Multivariate Outliers in Asset Returns and Risk Factors Data // SSRN Electronic Journal. 2017. doi: https://doi.org/10.2139/ssrn.3046092 

Guler K., Ng P. T., Xiao Z. Mincer-Zarnowitz quantile and expectile regressions for forecast evaluations under aysmmetric loss functions // Journal of Forecasting. 2017. Vol. 36, Issue 6. P. 651–679. doi: https://doi.org/10.1002/for.2462 

Dianawati F., Surjandari I., Nafitri R. Forecasting Methods for Determining the Level of Safety Stock in Electronic Industry // Industrial Engineering: Innovative Networks. 2012. P. 359–366. doi: https://doi.org/10.1007/978-1-4471-2321-7_40 

Agalarov Ya. M., Shorgin V. S. About the problem of profit maximization in g/m/1 queuing systems with threshold control of the queue // Informatics and Applications. 2017. Vol. 11, Issue 4. P. 55–64. doi: https://doi.org/10.14357/19922264170407 

Outamazirt A., Barkaoui K., Aissani D. Maximizing profit in cloud computing using M/G/c/k queuing model // 2018 International Symposium on Programming and Systems (ISPS). 2018. doi: https://doi.org/10.1109/isps.2018.8379008 

Strzęciwilk D., Zuberk W. M. Modeling and Performance Analysis of Priority Queuing Systems // Springer Series on Chemical Sensors and Biosensors. 2018. P. 302–310. doi: https://doi.org/10.1007/978-3-319-91186-1_31 

Sevastianov L. A., Vasilyev S. A. Large-scale queuing systems and services pricing // 2017 9th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). 2017. doi: https://doi.org/10.1109/icumt.2017.8255186 

Bahareh A., Nadia B. Determining supply chain safety stock level and location // Journal of Industrial Engineering and Management. 2014. Vol. 10, Issue 1. P. 42–71. doi: https://doi.org/10.3926/jiem.543 

Lutsenko I. Definition of efficiency indicator and study of its main function as an optimization criterion // Eastern-European Journal of Enterprise Technologies. 2016. Vol. 6, Issue 2 (84). P. 24–32. doi: https://doi.org/10.15587/1729-4061.2016.85453 

Lutsenko I. Identification of target system operations. Development of global efficiency criterion of target operations // Eastern-European Journal of Enterprise Technologies. 2015. Vol. 2, Issue 2 (74). P. 35–40. doi: https://doi.org/10.15587/1729-4061.2015.38963 

Development of the method for testing of efficiency criterion of models of simple target operations / Lutsenko I., Vihrova E., Fomovskaya E., Serdiuk O. // Eastern-European Journal of Enterprise Technologies. 2016. Vol. 2, Issue 4 (80). P. 42–50. doi: https://doi.org/10.15587/1729-4061.2016.66307 

Formal signs determination of efficiency assessment indicators for the operation with the distributed parameters / Lutsenko I., Fomovskaya E., Oksanych I., Vikhrova E., Serdiuk O. // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 1, Issue 4 (85). P. 24–30. doi: https://doi.org/10.15587/1729-4061.2017.91025 

Development of a verification method of estimated indicators for their use as an optimization criterion / Lutsenko I., Fomovskaya E., Oksanych I., Koval S., Serdiuk O. // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 2, Issue 4 (86). P. 17–23. doi: https://doi.org/10.15587/1729-4061.2017.95914 

Development of test operations with different duration in order to improve verification quality of effectiveness formula / Lutsenko I., Fomovskaya O., Vihrova E., Serdiuk O., Fomovsky F. // Eastern-European Journal of Enterprise Technologies. 2018. Vol. 1, Issue 4 (91). P. 42–49. doi: https://doi.org/10.15587/1729-4061.2018.121810 

Development of the method for modeling operational processes for tasks related to decision making / Lutsenko I., Oksanych I., Shevchenko I., Karabut N. // Eastern-European Journal of Enterprise Technologies. 2018. Vol. 2, Issue 4 (92). P. 26–32. doi: https://doi.org/10.15587/1729-4061.2018.126446 

Development of a method for the accelerated two-stage search for an optimal control trajectory in periodical processes / Lutsenko I., Fomovskaya O., Konokh I., Oksanych I. // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 3, Issue 2 (87). P. 47–55. doi: https://doi.org/10.15587/1729-4061.2017.103731 







Copyright (c) 2019 Igor Lutsenko, Illia Dmytriiev, Nina Avanesova, Iryna Semenyshyna, Zhanna Rozhnenko, Oleg Danileyko

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ISSN (print) 1729-3774, ISSN (on-line) 1729-4061