Production modelling in food sector with fuzzy parameters

Food is a strategic product that has a direct impact on the lives of society and individuals, and it has economic, environmental, and social dimensions. Food, which was used only for nutrition in ancient times, is used today for many different functions from entertainment to health. As a result, while the demand for food increases, at the same time food safety and quality expectations also increase. In order to meet these increasing demands and quality expectations at the local and global level, enterprises need to develop organizations in which they can produce larger amounts with, faster, and more flexible productions. Food is structurally suitable for fast consumption and perishable. Because of the asymmetric growth in the amount, speed, and flexibility of the food sector, the production of food waste is inevitable. Such a situation impairs sustainability by bringing economic and environmental costs to businesses, society, and individuals. The companies that produce daily meals in the food sector are identified as catering enterprises. Catering firms produce daily hot meals, fast food, and serves to restaurants, hotels, and similar food organizations. The supply, stock, production, and distribution activities of catering companies that respond wide range of demands are becoming very complex. When the perishable nature of the food products and the service speed expectations of the customers are considered, catering firms must provide high quality and agile production principles. Thus, this fact causes the costs of firms increase. In this study, the activities of storage and production in a catering company that produce daily meals were examined and the minimization of waste and activity costs arising from these activities was aimed. A two-stage mixed integer model was designed to solve the problem. In the second stage of the model that was designed under the assumption of certainty in the first stage, some parameters were transformed fuzzy. The fuzzy process helps to use the parameters within a range of values. With the two-stage model, stock, production and labor decisions were determined to minimize the total cost, while contributing to the reduction of food waste.