Table of Contents
Journal of Computational Engineering
Volume 2017, Article ID 2364254, 15 pages
Research Article

Analysis of MCLP, Q-MALP, and MQ-MALP with Travel Time Uncertainty Using Monte Carlo Simulation

1School of Distance Education, Universiti Sains Malaysia (USM), 11800 Gelugor, Penang, Malaysia
2School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia (UUM), 06010 Sintok, Kedah, Malaysia

Correspondence should be addressed to Norazura Ahmad; ym.ude.muu@aruzaron

Received 8 March 2017; Accepted 12 June 2017; Published 30 July 2017

Academic Editor: Fu-Yun Zhao

Copyright © 2017 Noraida Abdul Ghani and Norazura Ahmad. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper compares the application of the Monte Carlo simulation in incorporating travel time uncertainties in ambulance location problem using three models: Maximum Covering Location Problem (MCLP), Queuing Maximum Availability Location Problem (Q-MALP), and Multiserver Queuing Maximum Availability Location Problem (MQ-MALP). A heuristic method is developed to site the ambulances. The models are applied to the 33-node problem representing Austin, Texas, and the 55-node problem. For the 33-node problem, the results show that the servers are less spatially distributed in Q-MALP and MQ-MALP when the uncertainty of server availability is considered using either the independent or dependent travel time. On the other hand, for the 55-node problem, the spatial distribution of the servers obtained by locating a server to the highest hit node location is more dispersed in MCLP and Q-MALP. The implications of the new model for the ambulance services system design are discussed as well as the limitations of the modeling approach.