Titel
Design of an Optimal Robust Possibilistic Model in the Distribution Chain Network of Agricultural Products with High Perishability under Uncertainty
Autor*in
Amir Daneshvar
Department of Information Technology Management, Electronic Branch, Islamic Azad University
Reza Radfar
Department of Technology Management, Science and Research Branch, Islamic Azad University
... show all
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.
Stichwort
distribution network of agricultural productsrobust possibilistic optimizationperishabilityinventory controlmeta-heuristic algorithmuncertainty
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
phaidra.univie.ac.at/o:2023384
Erschienen in
Titel
Sustainability
Band
15
Ausgabe
15
ISSN
2071-1050
Erscheinungsdatum
2023
Publication
MDPI AG
Erscheinungsdatum
2023
Zugänglichkeit
Rechte
Rechteangabe
© 2023 by the authors
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