Optimization programming tools supporting supply chain management

• Autorzy: Szkutnik-Rogoż Joanna , Małachowski Jerzy

Identyfikatory

DOI

10.24425/bpasts.2023.145570

• Języki publikacji: EN

Abstrakty

EN

The issue of transportation is a particular type of mathematical programming that facilitates searching for and determining an optimal distribution network, considering the set of suppliers and recipients. This paper uses a numerical example to present a solution to a transport problem utilizing classical computation methods, i.e., the northwest corner, the least cost in a matrix, and the VAM approximation method. The objective of the paper was to develop tools in the form of algorithms that would then be implemented in three various computing environments (R, GNU Octave, and Matlab) that allow us to optimize transport costs within an assumed supply network. The model involved determining decision variables and indicating limiting conditions. Furthermore, the authors interpreted and visualized the obtained results. The implementation of the proposed solution enables users to determine an optimal transport plan for individually defined criteria.

Słowa kluczowe

EN

mathematical programming; optimization; supply chain

PL

programowanie matematyczne; optymalizacja; łańcuch dostaw

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2023
• Tom: Vol. 71, nr 3
• Strony: art. no. e145570
• Opis fizyczny: Bibliogr. 44 poz., rys., tab.

Twórcy

autor

Szkutnik-Rogoż Joanna

• Military University of Technology, Cybernetics Faculty, gen. Kaliskiego 2, 00-908 Warsaw, Poland

• https://orcid.org/0000-0001-9568-2291

autor

Małachowski Jerzy

• Military University of Technology, Faculty of Mechanical Engineering, gen. Kaliskiego 2, 00-908 Warsaw, Poland

• https://orcid.org/0000-0003-1300-8020

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).