Increased complexity and decentralized operations of farmers in China add to the management and control difficulties of the agricultural supply chain (ASC). Using a supply chain simulation is an effective way to investigate the robustness of the supply chain while considering uncertainties in the environment. This study proposed colored Petri nets to model the ASC with uncertainty risks, and the simulation model was able to give directions regarding the maximization of system performance by running different simulation experiments. Then, robust metric models were set up in regard to the delivery time and quantity of the supply chain. The entire system performance was analyzed through using these metric models. Finally, robust optimal strategies were investigated in order to maintain the robustness of the ASC by selecting a suitable partner quantity.
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