Integrated post-disaster medical assistance team scheduling and relief supply distribution

• Pages: 1279-1305
• DOI: https://doi.org/10.1108/IJLM-06-2017-0152
• Date: 05 June 2018
• Published date: 05 June 2018
• Author: Shengbin Wang,Feng Liu,Lian Lian,Yuan Hong,Haozhe Chen
• Subject Matter: Logistics,Management science & operations

Integrated post-disaster medical

assistance team scheduling and

relief supply distribution

Shengbin Wang

Department of Management and Marketing, College of Business,

University of Wisconsin–Eau Claire, Eau Claire, Wisconsin, USA

Feng Liu

School of Management Science and Engineering,

Dongbei University of Finance and Economics, Dalian, China

Lian Lian

School of Transportation and Logistics, Dalian University of Technology,

Dalian, China

Yuan Hong

Department of Computer Science, Illinois Institute of Technology,

Chicago, Illinois, USA, and

Haozhe Chen

Debbie and Jerry Ivy College of Business, Iowa State University, Ames, Iowa, USA

Abstract

Purpose –The purpose of this paper is to solve a post-disaster humanitarian logistics problem in which

medical assistance teams are dispatched and the relief supplies are distributed among demand points.

Design/methodology/approach –A mixed integer-programming model and a two-stage hybrid metaheuristic

method are developed to solve the problem. Problem instances of various sizes as well as a numerical example

based on the 2016 Kyushu Earthquake in Japan are used to test the proposed model and algorithm.

Findings –Computational results based on comparisons with the state-of-the-art commercial software show that

the proposed approach can quickly find near-optimal solutions, which is highly desirable in emergency situations.

Research limitations/implications –Real data of the parameters of the model are difficult to obtain.

Future collaborations with organizations such as Red Cross and Federal Emergency Management Agency

can be extremely helpful in collecting data in humanitarian logistics research.

Practical implications –The proposed model and algorithm can help governments and non-governmental

organizations (NGOs) to effectively and efficiently allocate and coordinate different types of humanitarian

relief resources, especially when these resources are limited.

Originality/value –This paper is among the first ones to consider both medical team scheduling (routing) and

relief aid distribution as decision variables in the humanitarian logistics field. The contributions include developing

a mathematical model and a heuristic algorithm, illustrating the model and algorithm using a numerical example,

and providing a decision support tool for governments and NGOs to manage the relief resources in disasters.

Keywords North America, Metaheuristics, Decision-making, Modelling, Asia, Logistics strategy,

Humanitarian logistics, Disaster medical assistance team routing, Computational study

Paper type Research paper

Nomenclature

Model parameters

Hset of DPs, where index is hand h¼

1;2;...;Hjj;h¼0 represents the MC;

Kset of DCs, where index is kand

k¼1;2;...;K

jj

;

O

k

set of relief medical supply orders received

at DC kfrom upstream suppliers, where

index is jand j¼1;2;...;Ok

jj

;∀k∈K

Iset of DMATs, where index is iand

i¼1;2;...;I

jj

;

The International Journal of

Logistics Management

Vol. 29 No. 4, 2018

pp. 1279-1305

© Emerald PublishingLimited

0957-4093

DOI 10.1108/IJLM-06-2017-0152

Received 15 June 2017

Revised 11 November 2017

27 January 2018

Accepted 15 February 2018

The current issue and full text archive of this journal is available on Emerald Insight at:

www.emeraldinsight.com/0957-4093.htm

1279

Post-disaster

medical

assistance

team

D

n

demand quantity for relief medical

supplies at DP h;∀h∈H

s

n

service operation time at DP h;∀h∈H

τ

nn

′time of a DMAT traveling from DP h

directly to DP h′;∀h,h′∈H

τ

0n

time of a DMAT traveling from MC

directly to DP h;∀h∈H

ω

kh

relief medical supply shipping time from

DC kto DP h;∀k∈K, j∈H

λ

kj

arrival time of the jth order of relief

medical supplies at DC k;∀k∈K,j∈O

k

C

kj

quantity capacity of the jth order of relief

medical supplies at DC k;∀k∈K,j∈O

k

La sufficiently large number

Decision variables

t

h

service starting time at DP h;∀h∈H

Q

kjh

supply quantity shipped from the jth

order of DC kto DP h;∀k∈K,j∈O

k

,h∈H

x

ihh

′equals 1 if team iserves DP h′

immediately after serving DP h, and 0

otherwise; 8iAI;h;h0A0fg[H;hah0

y

kjh

equals 1 if DP hreceives supplies from the

jth order of DC k, and 0 otherwise; ∀k∈K,

j∈O

k

,h∈H

1. Introduction

Natural disasters have always caused tremendous fatalities and damages across the world.

EM-DAT (www.emdat.be, retrieved on March 22, 2016) has reported that the annual number

of natural disasters has doubled during the past two decades in the world. In particular, 435

natural disasters occurred globally in Year 2010 alone, causing a total of 323,070 deaths and

$132.16 billion damage. A more recent disaster is the magnitude-7.3 earthquake in April

2016 that struck Kumamoto Prefecture, the south-western island of Kyushu in Japan, in

which approximately 180,000 people were affected and among them more than 3,000 needed

vital relief supplies and medical services (Brant, 2016). The critical importance of

humanitarian logistics in coping with such disasters cannot be overstated (Özdamar et al.,

2004; Özdamar and Demir, 2012; Gralla et al., 2014). Although the occurrences of natural

disasters are not preventable, effective preparedness and response can dramatically reduce

the property damages and human injuries and fatalities (Balcik et al., 2010; Celik et al., 2012;

Garrido et al., 2015). The primary objective in humanitarian logistics is to provide

beneficiaries with disaster relief supplies such as food, drinking water, medicine, tents,

surgeons (Cohen et al., 2014), ambulances (Gong and Batta, 2007), and vaccines, in a prudent

way to minimize the total number of casualties. However, relief resource and personnel

shortages often pose significant challenges in developing effective preparedness and

response strategies (Falasca and Zobel, 2012; Suzuki, 2012). In practice, relief supplies are

either stored in government or non-governmental organization (NGO) operated warehouses,

or transported to warehouses/distribution centers (DCs) from upstream suppliers in batch

orders (Ferrer et al., 2016). Each arrival order at a certain warehouse/DC has a limited

capacity, and it must be allocated to different shelters or demand points (DPs) immediately.

The remaining demand has to be met with orders arriving later.

Equally important is the efficient and effective provision of needed services in the

disaster response process. Many countries, such as USA, Canada, Turkey, Japan, and Israel,

use disaster medical assistance teams (DMATs) to provide these rescue and medical

services (Arziman, 2015). A DMAT is a group of professional medical personnel (doctors,

nurses, and technicians) organized by government to provide rapid-response medical care

during a man-made or natural disaster (https://en.wikipedia.org/wiki/Disaster_medical_

assistance_team, Retrieved on September 2, 2017). The members of DMATs have their

regular jobs when they are not called upon by the government for disaster relief efforts.

Once a disaster occurs, the government will determine the number of teams needed to be

dispatched to the affected area according to the severity of the disaster (Arziman, 2015).

The selected DMATs are then instructed to station at designated public facilities. Due to

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