Maximizing the service area: A criterion to choose optimal solution in the location of set covering problem

Location of set covering problem (LSCP) has attracted extensive attentions and studies because many emergency facility location problems could summarized to LSCP model in real-world life. Many methods - either optimal or heuristic - have been developed to obtain the solution. This paper focuses on the situation of multiple solutions. We argue that a solution with maximum service area is optimal, because such a solution could better cope with the future growth of demand points. With a larger service area, there is greater probability that the new added demand points fall within the current service area, and there is no need to build new facilities. The LSCP model is formulated as linear programming, and GIS functionality is called to find out the solution with maximum service area. The technique proved to be feasible by simulated data.