Designing a Mathematical Model to Solve the Uncertain Facility Location Problem Using C Stochastic Programming Method

• Autorzy: Chetthamrongchai Paitoon , Sayed Biju Theruvil , Artemova Elena Igorevna , Sharma Sandhir , Oudah Atheer Y. , Al-Nussairi Ahmed Kateb Jumaah , Bashar Bashar S. , Iswanto A. Heri

Identyfikatory

DOI

10.2478/fcds-2023-0014

• Języki publikacji: EN

Abstrakty

EN

Locating facilities such as factories or warehouses is an important and strategic decision for any organization. Transportation costs, which often form a significant part of the price of goods offered, are a function of the location of the plans. To determine the optimal location of these designs, various methods have been proposed so far, which are generally definite (non-random). The main aim of the study, while introducing these specific algorithms, is to suggest a stochastic model of the location problem based on the existing models, in which random programming, as well as programming with random constraints are utilized. To do so, utilizing programming with random constraints, the stochastic model is transformed into a specific model that can be solved by using the latest algorithms or standard programming methods. Based on the results acquired, this proposed model permits us to attain more realistic solutions considering the random nature of demand. Furthermore, it helps attain this aim by considering other characteristics of the environment and the feedback between them.

Słowa kluczowe

EN

location problem; mathematical model; meta-heuristic algorithms; service level; stochastic modeling

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 2023
• Tom: Vol. 48, No. 3
• Strony: 345--355
• Opis fizyczny: Bibliogr. 20 poz., tab.

Twórcy

autor

Chetthamrongchai Paitoon

• Faculty of Business Administration, Kasetsart University, Thailand

• https://orcid.org/0000-0002-9744-4358

autor

Sayed Biju Theruvil

• Department of Computer Science, Dhofar University, PO Box 2509, PCode 211, Salalah, Sultanate of Oman

• https://orcid.org/0000-0002-9675-4872

autor

Artemova Elena Igorevna

• Department of Economic Theory, Head of the Department, Kuban State Agrarian University Named after I.T. Trubilin, Krasnodar, Russian Federation, 350044, Krasnodar, Kalinina Street, 13.

• https://orcid.org/0000-0002-4168-6112

autor

Sharma Sandhir

• Ph.D. in Management, Chitkara Business School, Faculty of Business Management, Chitkara University, Punjab, India

• https://orcid.org/0000-0002-3940-8236

autor

Oudah Atheer Y.

• Department of Computer Sciences, College of Education for Pure Science, University of Thi-Qar, Iraq

• https://orcid.org/0000-0003-0867-7203

autor

Al-Nussairi Ahmed Kateb Jumaah

• Al-Manara College For Medical Sciences, Maysan, Iraq

• https://orcid.org/0000-0001-6090-2725

autor

Bashar Bashar S.

• Al-Nisour University College, Baghdad, Iraq

• https://orcid.org/0000-0001-5518-4888

autor

Iswanto A. Heri

• Public Health Department, Faculty of Health Science, University of Pembangunan Nasional Veteran Jakarta, Jakarta, Indonesia

• https://orcid.org/0000-0002-1102-0176

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).