چكيده به لاتين
Abstract:
In this research, we dealt with the integrated design of the agricultural products supply chain considering the quality of products and time constraints (planting and harvesting seasons) under uncertainty conditions. The aim is to provide a robust mathematical model for agrifood food supply chain (AFSC) in the planting, harvesting, processing, and storage, which includes locating decisions, inventory and distribution. The research want to find the robut solutions for managing transportation and storage, cultivating, harvesting, processing, and distributing products to the market in order to maximize the AFCS profit. In addition, the freshness (quality) of products during the transportation and storage processes is considered to be variable. Mathematical programming approaches are used to solve the problem and three mathematical models nominal programming (EV), scenario-based stochatics programming (SSP), robust scenario-based stochatics programming (RSSP) to solve the development problem, and CPLEX is used to implete the models. In the RSSP approach, which is also known as the Mulvey model, the system expect performance is considered as the robust solution or optimality robustness, although sometimes the deviation of the objective values are added to the model. In addition, the constraints are flexible, which allows a lower chance of constraint to the extent to improve both the system explext performance and the deviation of responses. After applying proposed approach and comparing theirs solutions with the optimal response of each scenario, it is seen that in more likely scenarios, the absolute and relative deviation of the cost is lower and this leads to a reduction in the standard deviation of profits in different scenarios. Therefore, according to the numerical result of this study, proposed RSSP approach obtains a robust solution whis is very close to its optimal value and moreover, the standard deviation of responses is controlled.
Keywords:
Agri-Food Supply Chain; Scenario based Stochastic Programming; Robust Optimization; Price Dependent on Quality; Time Window