A novel multi-objective robust fuzzy stochastic programming model for sustainable agri-food supply chain: case study from an emerging economy

On the one hand, supply chain management of agri-food products under uncertain conditions has a significant impact on food security and, on the other hand, increases the profits of supply chain components. Moreover, considering the sustainability concepts leads to more social and environmental benef...

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Vydané v:Environmental science and pollution research international Ročník 30; číslo 25; s. 67398 - 67442
Hlavní autori: Rahbari, Misagh, Khamseh, Alireza Arshadi, Mohammadi, Mohammad
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2023
Springer Nature B.V
Predmet:
Agribusiness
Agricultural production
Aquatic Pollution
Atmospheric Protection/Air Quality Control/Air Pollution
Canned food
canned foods
Carbon
case studies
Confidence intervals
Consumer Behavior
Customers
Earth and Environmental Science
Ecotoxicology
Environment
Environmental Chemistry
Environmental degradation
Environmental Health
environmental markets
Environmental science
Farms
Food
Food chains
Food security
Food Supply
food supply chain
Multiple objective analysis
Optimization
Parameter sensitivity
prices
Research Article
Robustness (mathematics)
Sensitivity analysis
Stochastic models
Stochastic programming
supply chain management
Supply chains
Sustainability
system optimization
Uncertainty
Waste Water Technology
Water Management
Water Pollution Control
Agri-food supply chain
Robust fuzzy stochastic programming
Carbon cap and trade mechanism
Canned food
Sustainability
ISSN:1614-7499, 0944-1344, 1614-7499
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Shrnutí:On the one hand, supply chain management of agri-food products under uncertain conditions has a significant impact on food security and, on the other hand, increases the profits of supply chain components. Moreover, considering the sustainability concepts leads to more social and environmental benefits. The present study investigates the canned food supply chain under uncertain conditions and sustainability concepts by considering strategic and operational decisions and different characteristics. The proposed model is a multi-echelon, multi-period, multi-product, multi-objective location-inventory-routing problem (LIRP) in which the vehicle fleet is considered heterogeneously. The objectives of this model are to (1) minimize costs, (2) minimize customer dissatisfaction, (3) maximize production throughput, and (4) maximize job opportunities. In this study, carbon cap and trade mechanism are used to minimize environmental damage. Robust fuzzy stochastic programming (RFSP) is employed to cope and control uncertainties. The multi-objective optimization problem is implemented on a real case and solved using the Torabi and Hassini (TH) method. The results of this study showed that with increasing confidence levels, the severity of the problem increased and the values of the objective functions worsened. Also, using the relative value of stochastic solution (RVSS) criterion demonstrated that the effect of utilizing the RFSP approach on the first and second objective functions was higher than that the nominal approach showed itself. Finally, sensitivity analysis is performed on two parameters: the selling price of products to foreign customers and the cost of purchasing products from farms. The results of this study showed that changing these two parameters had a significant effect on the first and second objective functions.
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ISSN:1614-7499
0944-1344
1614-7499
DOI:10.1007/s11356-023-26305-w