Article ID: | iaor20114876 |
Volume: | 24 |
Issue: | 2 |
Start Page Number: | 110 |
End Page Number: | 130 |
Publication Date: | Jun 2011 |
Journal: | OR Insight |
Authors: | Chipulu Max, Ojiako Udechukwu, Downing Matthew, Kaparis Konstantinos |
Keywords: | forecasting: applications, inventory |
The locations of emergency medical service and fire stations are of paramount importance in order to achieve an effective and reliable emergency response system. As communities grow and demographics change, it may become necessary to replace existing stations or add more stations to satisfy the increasing public demands for emergency responses. With its fast growing population, new urban developments, and heavy traffic conditions, the location planning problem for new fire stations has recently gained greater importance for the City of Istanbul. In this article, we describe an integer programming-based approach to address this problem. We formulate the problem as a dynamic risk-based multiple coverage model. In this model, the demand regions are required to be serviced from two or three stations within the desired time limits according to the risk categories they are associated with. We first identify the risk category of each region and then solve the model to optimally determine the locations for the new fire stations. The results show that new fire stations can be sited more effectively utilizing the described optimization approach.