Investigating a citrus fruit supply chain network considering CO2 emissions using meta-heuristic algorithms

Fariba Goodarzian (), Vikas Kumar () and Peiman Ghasemi ()
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Fariba Goodarzian: University of Seville, Camino de los Descubrimientos s/n
Vikas Kumar: University of the West of England
Peiman Ghasemi: German University of Technology in Oman (GUtech)

Annals of Operations Research, 2025, vol. 354, issue 2, No 3, 547-603

Abstract: Abstract According to the increasing carbon dioxide released through vehicles and the shortage of water resources, decision-makers decided to combine the environmental and economic effects in the Agri-Food Supply Chain Network (AFSCN) in developing countries. This paper focuses on the citrus fruit supply chain network. The novelty of this study is the proposal of a mathematical model for a three-echelon AFSCN considering simultaneously CO2 emissions, coefficient water, and time window. Additionally, a bi-objective mixed-integer non-linear programming is formulated for production–distribution-inventory-allocation problem. The model seeks to minimise the total cost and CO+ emission simultaneously. To solve the multi-objective model in this paper, the Augmented Epsilon-constraint method is utilised for small- and medium-sized problems. The Augmented Epsilon-constraint method is not able to solve large-scale problems due to its high computational time. This method is a well-known approach to dealing with multi-objective problems. It allows for producing a set of Pareto solutions for multi-objective problems. Multi-Objective Ant Colony Optimisation, fast Pareto genetic algorithm, non-dominated sorting genetic algorithm II, and multi-objective simulated annealing are used to solve the model. Then, a hybrid meta-heuristic algorithm called Hybrid multi-objective Ant Colony Optimisation with multi-objective Simulated Annealing (HACO-SA) is developed to solve the model. In the HACO-SA algorithm, an initial temperature and temperature reduction rate is utilised to ensure a faster convergence rate and to optimise the ability of exploitation and exploration as input data of the SA algorithm. The computational results show the superiority of the Augmented Epsilon-constraint method in small-sized problems, while HACO-SA indicates that is better than the suggested original algorithms in the medium- and large-sized problems.

Keywords: Citrus fruit agri-food supply chain network; CO2 emissions; Mathematical model; Meta-heuristic algorithms (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10479-022-05005-7

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