A bi-objective stochastic single facility location model for a supermarket

Abstract

One of the important strategic challenges in today’s competitive environment is to select the best location for new facilities. Selecting a new location is vital for retail stores such as chain supermarkets and can be considered as a huge competitive advantage which may result in their failure or success. Location models are hard to implement in the real world problems, firstly because of the uncertainty of the input parameters and secondly, due to the intensive computations involved when the solution space is large such as a city. In this study, a stochastic biobjective model is developed for points and area destinations with the purpose of finding a single new location for a chain supermarket that aims to be close to more customers and also have the minimum number of competitors near to the new location. Customer locations are considered to be regional with uniform probability distribution. A reduced gradient solution procedure is used as an algorithm for solving the model. The problem is solved with the help of Matlab software due to the high computations involved. The result of this study shows that more firms and companies can be drawn to actually implementing these models that are closer to reality to increase their profit and minimize their cost which is the aim of all business firms.