<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</abstract>

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.

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

Professor, Doctor of Economics, Department of Economic Theory, Head of the Department

Kuban State Agrarian University Named after I.T. Trubilin, Krasnodar

Ph.D. in Management, Chitkara Business School, Faculty of Business Management

Department of Computer Sciences, College of Education for Pure Science

Public Health Department, Faculty of Health Science

University of Pembangunan Nasional Veteran Jakarta

Foundations of Computing and Decision Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Locating facilities such as factories or warehouses is an important and strategic decision for any organization. Transportation costs, which often form a...

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

Pubblicato online: 05 ott 2023

Pagine: 345 - 355

Ricevuto: 16 lug 2022

Accettato: 14 mag 2023

DOI: https://doi.org/10.2478/fcds-2023-0014

Parole chiave
location problem, mathematical model, meta-heuristic algorithms, service level, stochastic modeling

© 2023 Paitoon Chetthamrongchai et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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

Pubblicato online: 05 ott 2023

Pagine: 345 - 355

Ricevuto: 16 lug 2022

Accettato: 14 mag 2023

DOI: https://doi.org/10.2478/fcds-2023-0014

Parole chiavelocation problem, mathematical model, meta-heuristic algorithms, service level, stochastic modeling

© 2023 Paitoon Chetthamrongchai et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
location problem, mathematical model, meta-heuristic algorithms, service level, stochastic modeling