Volume 39, Number 3, July-September 2005
|Page(s)||143 - 162|
|Published online||25 January 2006|
Allocating servers to facilities, when demand is elastic to travel and waiting times
Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Vicuna Mackenna 4860, Santiago, Chile; firstname.lastname@example.org; email@example.com
2 Graduate Program, Department of Systems Engineering, Pontificia Universidad Catolica de Chile, Vicuna Mackenna 4860, Santiago, Chile; FBarros@sqm.cl
Accepted: 19 September 2005
Public inoculation centers are examples of facilities providing service to customers whose demand is elastic to travel and waiting time. That is, people will not travel too far, or stay in line for too long to obtain the service. The goal, when planning such services, is to maximize the demand they attract, by locating centers and staffing them so as to reduce customers' travel time and time spent in queue. In the case of inoculation centers, the goal is to maximize the people that travel to the centers and stay in line until inoculated. We propose a procedure for the allocation of multiple servers to centers, so that this goal is achieved. An integer programming model is formulated. Since demand is elastic, a supply-demand equilibrium equation must be explicitly included in the optimization model, which then becomes nonlinear. As there are no exact procedures to solve such problems, we propose a heuristic procedure, based on Heuristic Concentration, which finds a good solution to this problem. Numerical examples are presented.
Mathematics Subject Classification: 90B80 / 90B22
Key words: Facility location / resource allocation / nonlinear optimization / integer programming / heuristics.
© EDP Sciences, 2006
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.