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A fuzzy queuing facility location model with ant colony optimization algorithm for large-scale emergencies

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3 Author(s)
Xiang-lin Lu ; Coll. of Econ. & Manage., CAU, Beijing, China ; Hou Yun-xian ; Shen Qiang

Efficient and timely response during accidents has received increased attention from practitioners and researchers. The sitting of emergency service facilities plays a crucial role in determining the efficiency of safety protection and emergency response. This article presents a fuzzy location-allocation model for large-scale emergencies. The previous efforts in this area have concentrated on enhancing the reliability and quality of service with a probabilistic orientation. However, this research does not typically address the particular conditions that arise when locating facilities to service large-scale emergencies, such as earthquakes, terrorist attacks, etc. In this paper we utilize fuzzy theory to develop a queuing maximal covering location-allocation model which we call the fuzzy queuing maximal covering location-allocation model for determining the facility locations in response to large-scale emergencies. ACO algorithm is developed to solve and test the model through a large-scale emergency example. We also propose extensions to our model.

Published in:

Service Systems and Service Management (ICSSSM), 2010 7th International Conference on

Date of Conference:

28-30 June 2010