Addressing a set of meta-heuristics to solve a multi-objective model for closed-loop citrus supply chain considering CO2 emissions

摘要: Abstract Nowadays, the agricultural supply chain as one of key fields food production is considered which has recently attracted much attention from researchers. This paper focuses on optimizing a closed-loop citrus chain. To this end, multi-objective mathematical model formulated that it attempts to minimize total costs, maximize demands' responsiveness, and CO2 emissions environmental damages. solve proposed model, five meta-heuristic algorithms include version published algorithm called tree growth (MOTGA) four well-known NSGA-II, NRGA, MOKA, MOSA are utilized. It should be noted these tuned using Taguchi method achieve better performance validated e-constraint in small size examples. shows cannot large problems implies NP-hardness problem. Moreover, MOTGA selected best approach with least distance ideal point. Finally, more measurement, sensitivity analysis performed results confirmed efficiency algorithms. Based results, shown multiple transportation vehicles can reduce improved all objective functions’ values. In addition, considering responsiveness by about 14%. So, two new assumptions lead improve demand reductions.