Design of an Optimal Robust Possibilistic Model in the Distribution Chain Network of Agricultural Products with High Perishability under Uncertainty

Amir Daneshvar, Reza Radfar, Peiman Ghasemi (), Mahmonir Bayanati and Adel Pourghader Chobar
Additional contact information
Amir Daneshvar: Department of Information Technology Management, Electronic Branch, Islamic Azad University, Tehran 1477893855, Iran
Reza Radfar: Department of Technology Management, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran
Peiman Ghasemi: Department of Business Decisions and Analytics, University of Vienna, Kolingasse 14-16, 1090 Vienna, Austria
Mahmonir Bayanati: Department of Management, Faculty of Technology and Industrial Management, West Tehran Branch, Islamic Azad University, Tehran 1477893855, Iran
Adel Pourghader Chobar: Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin 3471993116, Iran

Sustainability, 2023, vol. 15, issue 15, 1-22

Abstract: In this article, the modeling of a distribution network problem of agricultural products with high perishability under uncertainty is discussed. The designed model has three levels of suppliers, distribution centers, and retailers, in which suppliers can directly or indirectly meet retailers’ demand. Due to agricultural product distribution network unpredictability, robust possibilistic optimization (RPO) has been applied. This model is innovative and takes uncertainty into account. The findings show that uncertainty increases network demand. Supply, distribution, maintenance, and order expenses have grown. By examining the rate of perishability of agricultural products, it has been revealed that, with the growth of this rate, the costs have increased according to the ordering and spoilage of the products. The genetic algorithm (GA), whale optimization algorithm (WOA), and arithmetic optimization algorithm (AOA) have also been applied to analyze the model. The calculations on 10 sample problems in larger sizes show that the AOA has the best performance in achieving near-optimal solutions. Conversely, the WOA has the lowest computing time compared to other meta-heuristic algorithms. Additionally, the statistical test results show no significant difference between the average calculation time and the objective function among the applied algorithms.

Keywords: distribution network of agricultural products; robust possibilistic optimization; perishability; inventory control; meta-heuristic algorithm; uncertainty (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/15/11669/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/15/11669/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:15:p:11669-:d:1205068

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().