Mushroom Supply Chain Network Design Using Robust Optimization Approach under Uncertainty

Nowadays, attention to sustainable food security and health and the incentive to increase revenue, has led many governments and policymakers to pay special attention to the effective performance of the agricultural supply chain. The positive effects of paying attention to agricultural supply chain management can be easily seen in job creation in urban and rural areas, easy access to the market for agricultural retailers and the appropriate relationship between small and medium businesses. This study examines the complete supply chain network of agricultural products (mushroom industry) in uncertain conditions. The model is presented in the form of two general objectives; the first objective refers to minimizing network costs, and the second objective to minimizing network environmental pollutants. Also, the proposed model is in uncertain conditions, and to overcome the uncertainty model, the optimization approach has been used. Finally, due to the multi-objective nature of the proposed model, the reinforced epsilon-constraint solution approach is used. Simulated data has been utilized to validate the proposed robust model. Given the results, the recycling rate of the consumed compost was above 0.4, demonstrating that applying a closed-loop supply chain network is logical, and establishing a recycling center could be economically justified.