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Title of Journal: J Comb Optim

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Abbravation: Journal of Combinatorial Optimization

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Springer US

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DOI

10.1016/0734-9750(92)90602-6

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1573-2886

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A twostage method for member selection of emergen

Authors: Xi Chen Zhiping Fan Zhiwu Li Xueliang Han Xiao Zhang Haochen Jia
Publish Date: 2015/03/24
Volume: 30, Issue: 4, Pages: 871-891
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Abstract

Member selection is an important decision making problem in the formation of emergency medical teams It involves selecting an optimal combination from a reasonable number of doctors nurses and emergency medical technicians Selecting suitable members for a medical emergency team MET will facilitate the effectiveness of emergency medical service EMS Essentially investigations on EMS could offer models which increase the efficiency of proper matching and earn time to save lives The existing methods for member selection pay much attention to the individual information to measure the individual performance of members while few studies focus on the collaborative information to measure the collaborative performance between members This paper aims to propose a twostage method for member selection of an MET In the first stage knowledge rules are proposed to identify the valid candidates quickly In the second stage the individual information of members the collaborative information between members and the response time of EMS are all considered to build a threeobjective 01 programming model Due to its intractability the model is solved by a nondominated sorting genetic algorithm II Liberia now suffering the Ebola virus is used as a backdrop for this study A practical example followed by a computational simulation experiment is used to illustrate the applicability and the effectiveness of the proposed methodThis work was partially supported by the National Natural Science Foundation of China under Grants 71101114 71473188 71401131 71403158 and 61374068 China Postdoctoral Science Foundation under Grant 2012M511979 the Fundamental Research Funds for the Central Universities under Grants BDY251412 and the Science and Technology Development Fund MSAR under Grant 066/2013/A2

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