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

Abstract According to the increasing carbon dioxide released through vehicles and shortage of water resources, decision-makers decided combine environmental economic effects in Agri-Food Supply Chain Network (AFSCN) developing countries. This paper focuses on citrus fruit supply chain network. The novelty this study is proposal a mathematical model for three-echelon AFSCN considering simultaneously CO 2 emissions, coefficient water, time window. Additionally, bi-objective mixed-integer non-linear programming formulated production–distribution-inventory-allocation problem. seeks minimise total cost + emission simultaneously. To solve multi-objective paper, Augmented Epsilon-constraint method utilised small- medium-sized problems. not able large-scale problems due its high computational time. well-known approach dealing with It allows producing set Pareto solutions Multi-Objective Ant Colony Optimisation, fast genetic algorithm, non-dominated sorting algorithm II, simulated annealing are used model. Then, hybrid meta-heuristic called Hybrid Optimisation Simulated Annealing (HACO-SA) developed In HACO-SA an initial temperature reduction rate ensure faster convergence optimise ability exploitation exploration as input data SA algorithm. results show superiority small-sized problems, while indicates that better than suggested original algorithms medium- large-sized