@techreport{TD:100934,
	att_abstract={{Background

The routes to collect blood samples for analysis must be designed in a cost-efficient manner
while satisfying two important constraints: (i) two-hour time windows between collection and
delivery, and (ii) vehicle capacity.

Purposes

The purpose of this work is to develop a method to find blood sample collection routes that
minimize transportation costs and satisfy the problem constraints.

Methodology

We applied a state-of-the-art metaheuristic based on a genetic algorithm to solve the
problem of blood sample collection in one of the largest clinical laboratories in Spain.
We implemented our algorithm using C programming where the user, for each collection
point, enters the following information: postal address, average collecting time, and average
demand (in thermal containers). In few seconds, our program obtains collection routes
that specify the collection sequence for each vehicle. Two different types of vehicles were
considered with capacity of 16 and 25 thermal containers, respectively. Unless new collection
points are added or problem parameters are changed substantially, routes need to be designed
only once.

Findings

The laboratory used to plan routes manually for 43 collection points, having ten different
routes covered by an external carrier company. With the implementation of this method, we
could reduce the number of routes to seven, which represents annual savings of €45,000 in
transportation.

Implications

Our method designs blood collection routes with reduced costs that meet the time and
capacity constraints of the problem. This can be easily implemented in other laboratories that
face this type of problem. The method is particularly interesting and useful as the number of
collection points increases.}},
	att_authors={mr5626},
	att_categories={C_CCF.7},
	att_copyright={{BioMed Central}},
	att_copyright_notice={{The definitive version was published in  2014{{, 2014-01-09}}{{, http://dx.doi.org/10.1186/1472-6963-14-12}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={Blood Sample Transportation,  Vehicle Routing Problem,  Genetic Algorithm,  Operations Research},
	att_techdoc={true},
	att_techdoc_key={TD:100934},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100934_DS1_2012-07-20T18:51:20.403Z.pdf},
	author={Mauricio Resende and Helena R. Lourenço and Luciana S. Pessoa and Alec Grasas and Imma Caballé and Nuria Barba},
	institution={{BMC Health Services Research}},
	month={January},
	title={{On the Improvement of Blood Sample Collection at a Clinical Laboratory}},
	year=2014,
}