a fuzzy chance-constrained programming model for integrated planning of the wheat supply chain considering wheat quality and sleep period: a case study

Wheat is a staple food in many countries, and as a result, the first most cultivated crop worldwide. since wheat is a vital product in terms of food security, and its supply chain needs to be studied and planned carefully. this paper proposes a mixed-integer linear programming model for integrated planning of imported and domestically-produced wheat that addresses supplier selection, order planning, transportation, storage, and distribution problems at the same time. specifically, this model focuses on the wheat quality and wheat sleep period. moreover, differentiation of long-term and short-term storage facilities and consideration of intra-layer flows between storage facilities are other characteristics of this model. a fuzzy chance-constrained programming approach is employed to cope with the uncertainties associated with domestic supply, demand, and global wheat prices. applicability and advantages of the developed model are demonstrated using real data from the wheat supply chain of iran. results show that the current status of the wheat supply chain of iran is far from being optimal, and there are many opportunities for improvement.