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Optimisation Models for Inventory Management with Limited Number of Stock Items

Author

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  • Julian Vasilev

    (Department of Informatics, University of Economics Varna, 9002 Varna, Bulgaria)

  • Tanka Milkova

    (Department of Statistics and Applied Mathematics, University of Economics Varna, 9002 Varna, Bulgaria)

Abstract

Background : Stocks of raw materials and finished products are found in all units of logistics systems and require significant financial means of management. For this reason, scientifically justified approaches to stock management and cost minimisation must be explored. Despite the existence of many such approaches in literature and practice, each case has its own specificities and specificities to which stock management models should be adapted. In this article, the aim of the authors is to propose an approach to determine optimal supply sizes from different types of stocks (more than one is known in the literature as multi-nomenclature) that minimises only the cost of inventory management. The cost of inventory is not included. Methods : The article used the methods of mathematical optimisation, the method of least squares, and regression analysis. The scope of the models in the article is inventory management, with a limited number of stock keeping units. Time series data for the delivered quantities and time series data for the costs of stock management are used. Both time series use the same time period. Results : The constructed specific nonlinear mathematical models for optimising the total cost of stock management are approbated based on sample data and the results obtained are analysed. Conclusions : The created mathematical models and methods for optimising the total cost of stock management may be used by logistics managers to minimise the total costs of inventory management.

Suggested Citation

  • Julian Vasilev & Tanka Milkova, 2022. "Optimisation Models for Inventory Management with Limited Number of Stock Items," Logistics, MDPI, vol. 6(3), pages 1-12, August.
    • Handle: RePEc:gam:jlogis:v:6:y:2022:i:3:p:54-:d:877625
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    References listed on IDEAS

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    1. Plamena Milusheva, 2014. "Development of the logistics in hotels on the Bulgarian Black Sea coast," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, issue 1, pages 92-97, November.
    2. Plamena Milusheva, 2019. "Some aspects of the decision to buy, not to produce parts and components," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 2, pages 64-67.
    3. Plamena Milusheva, 2016. "Aspects Of The Relationships Of The Companies With The Suppliers," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 1, pages 6-10.
    4. Nita H. Shah & Ekta Patel & Kavita Rabari, 2022. "Investigation of carbon emissions due to COVID-19 vaccine inventory," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 409-420, February.
    5. Plamena Milusheva, 2020. "Challenges To Supply Construction Companies In Conditions Of Pandemic," Economic Science, education and the real economy: Development and interactions in the digital age, Publishing house Science and Economics Varna, issue 1, pages 233-237.
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    Cited by:

    1. Rushikesh A. Patil & Abhishek D. Patange & Sujit S. Pardeshi, 2023. "International Transportation Mode Selection through Total Logistics Cost-Based Intelligent Approach," Logistics, MDPI, vol. 7(3), pages 1-26, September.
    2. Julian Vasilev (ed.), 2023. "Digitalization, big data and business intelligence," Digitization, big data, artificial intelligence, Publishing house "Science and Economics" Varna, number 24, September.

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