Mathematical models for locating sales offices in Turkey for an apparel textile and fashion industry

Growth of the trade volume in the world and in Turkey, continuous participation of new actors and the challenging competitive terms have caused rapid development in retail sector. Companies are developing tighter policies and strategies to achieve more sales and higher turnover rates in their processes to increase their competitiveness. Therefore, they have to take realistic decisions based on scientific methods. Retailing consists of five main processes namely supply, inventory management, retail chain management, sales and after-sales services. Although, there are decision models currently available in the literature that can be utilized in optimizing processes internally, all processes have to be considered together to maximize utility since decisions taken in each process have an impact on the decision mechanisms of other processes. Accordingly, the aim of this thesis is to develop a decision support system that tackles all processes as a whole by constructing a Linear Mathematical Programming Model that maximizes corporate profits. It is aimed to take all critical decisions including opening new stores and/or closing down and/or restoring existing stores by considering the entire system. Within this context, sales forecasting is one of the most important inputs to the model. This, however, constitutes a problem for the locations at which to open up new stores since they do not have past sales data and the literature involves very few studies on this issue. Therefore, potential quantity of sales is forecast via Regression model by implementing Huff Gravity Method used in forecasting the amount of potential customer in literature. This, by itself, contributes to the literature. The developed model is validated by the use of a retail company's data and found applicable.