| Title | Metaheuristic algorithms for a sustainable agri-food supply chain considering marketing practices under uncertainty |
|---|---|
| ID_Doc | 67058 |
| Authors | Gholian-Jouybari, F; Hashemi-Amiri, O; Mosallanezhad, B; Hajiaghaei-Keshteli, M |
| Title | Metaheuristic algorithms for a sustainable agri-food supply chain considering marketing practices under uncertainty |
| Year | 2023 |
| Published | |
| Abstract | In recent decades, the rapid growth of the global population has caused a significant increase in agricultural and food product demands. Thereby, the production of various items in the agricultural food supply chain network has increased to diminish food security concerns. On the other hand, the excessive production of products has led to various issues, such as greenhouse gas emissions and increased water consumption in farmlands, followed by supply chain-related challenges affecting the intermediaries in the next network levels. In this study, an agricultural food supply chain network under marketing practices is firstly probed by developing a stochastic multiobjective programming model to effectively improve three main pillars of sustainability. A convex robust optimization approach addresses the uncertainty of the farm production capacity and the saffron demands in the supply network. The effectiveness of the proposed mathematical model is certified by a case study on saffron business using the LP-metric method. A metaheuristic-oriented methodology comprising a modified Keshtel Algorithm is adapted to deal with the NP-hardness of the problems. The performance of the proposed solution methods is evaluated by two strategies, a statistical comparison and a supportive tool developed based on multicriteria decision-making (MCDM) methods. The results validate the capability of the applied algorithms to solve the problem in different dimensions. Moreover, the MCDM method approves that MOKASEO outclassed in small, medium, and large-sized problems compared to other algorithms. |
Similar Articles
| ID | Score | Article |
|---|---|---|
16145
|
Gholian-Jouybari, F; Hajiaghaei-Keshteli, M; Bavar, A; Bavar, A; Mosallanezhad, B A design of a circular closed-loop agri-food supply chain network-A case study of the soybean industry(2023) | |
| 63894
|
Drofenik, J; Pahor, B; Kravanja, Z; Pintaric, ZN Multi-objective scenario optimization of the food supply chain - Slovenian case study(2023) | |
| 72862
|
Seydanlou, P; Jolai, F; Tavakkoli-Moghaddam, R; Fathollahi-Fard, AM A multi-objective optimization framework for a sustainable closed-loop supply chain network in the olive industry: Hybrid meta-heuristic algorithms(2022) | |
| 76823
|
Xie, S; Formonov, A; Thapit, AA; Alshalal, MH; Obeis, MKS; Sivaraman, R; Jabbar, AH; Chaudhary, P; Mustafa, YF Mushroom Supply Chain Network Design Using Robust Optimization Approach under Uncertainty(2022)Industrial Engineering And Management Systems, 21, 3 | |
| 73272
|
Naderi, R; Nikabadi, MS; Tabriz, AA; Pishvaee, MS Supply chain sustainability improvement using exergy analysis(2021) | |
| 4467
|
Baratsas, SG; Pistikopoulos, EN; Avraamidou, S A systems engineering framework for the optimization of food supply chains under circular economy considerations(2021) | |
| 22528
|
Ali, H; Zhang, JW; Shoaib, M A hybrid approach for sustainable-circular supplier selection based on industry 4.0 framework to make the supply chain smart and eco-friendly(2024)Environment Development And Sustainability, 26.0, 9 | |
| 73281
|
Pourjavad, E; Mayorga, RV Multi-objective Fuzzy Programming of Closed-Loop Supply Chain Considering Sustainable Measures(2019)International Journal Of Fuzzy Systems, 21, 2 | |
| 3710
|
Prajapati, D; Zhou, FL; Dwivedi, A; Singh, T; Lakshay, L; Pratap, S Sustainable Agro-Food Supply Chain in E-Commerce: Towards the Circular Economy(2022)Sustainability, 14, 14 | |
| 5012
|
Foroozesh, N; Karimi, B; Mousavi, SM; Mojtahedi, M A hybrid decision-making method using robust programming and interval-valued fuzzy sets for sustainable-resilient supply chain network design considering circular economy and technology levels(2023) |