Abstract
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, firstly because of the uncertainties 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 bi-objective model is developed for point 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 have the minimum number of competitors near to the new location. Customer locations are considered to be regional with a 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 the MATLAB software due to the high computations involved.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Services and Operations Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
