Abstract:
Facility location problems constitute an area of study that has been extensively researched due to the opportunities presented for small businesses and corporations to increase their efficiency and profitability. Numerous models have been developed in an attempt to find solutions to such problems; two of these include the set-covering problem (SCP) and the maximal covering location problem (MCLP). Applications of these two covering models have been used to find optimal locations for public and private facilities such as fire stations, police stations and retail stores. This study applies the SCP and MCLP to find good locations for bike sharing stations in the City of Richmond. Multiple iterations of the SCP and MCLP for Bike Stations models are performed for each of the individual “bike demand” criteria, along with additional iterations using various combinations of service distances and station numbers. Each of these iterations provide varying results of demand covered; station recommendations are made using a combined analysis, and suggestions for model improvements and future applications are discussed.
