TY - GEN
T1 - A clustering optimization approach for disaster relief delivery
T2 - 3rd Annual International Symposium on Information Management and Big Data, SIMBig 2016
AU - Vargas-Florez, Jorge
AU - Medina-Rodríguez, Rosario
AU - Alva-Cabrera, Rafael
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - During the last decade, funds to face humanitarian operations have increased approximately ten times. According to the Global Humanitarian Assistance Report, in 2013 the humanitarian funding requirement was by US$ 22 billion, which represents 27.2% more than the requested in 2012. Furthermore, the transportation cost represents between one-third to two-thirds from the total logistics cost. Therefore, a frequent problem in a disaster relief is to reduce the transportation cost by keeping an adequate distribution service. The latter depends on a reliable delivery route design, which is not easy to do considering a post-disaster environment, where the infrastructures and sources could be inexistent, unavailable or inoperative. This paper tackles this problem, regarding the constraints, to deliver relief aids in a post-disaster state (like an eight-degree earthquake) in the capital of Perú. The routes found by the hierarchical ascending clustering approach, solved with a heuristic model, achieved a sufficient and satisfactory solution.
AB - During the last decade, funds to face humanitarian operations have increased approximately ten times. According to the Global Humanitarian Assistance Report, in 2013 the humanitarian funding requirement was by US$ 22 billion, which represents 27.2% more than the requested in 2012. Furthermore, the transportation cost represents between one-third to two-thirds from the total logistics cost. Therefore, a frequent problem in a disaster relief is to reduce the transportation cost by keeping an adequate distribution service. The latter depends on a reliable delivery route design, which is not easy to do considering a post-disaster environment, where the infrastructures and sources could be inexistent, unavailable or inoperative. This paper tackles this problem, regarding the constraints, to deliver relief aids in a post-disaster state (like an eight-degree earthquake) in the capital of Perú. The routes found by the hierarchical ascending clustering approach, solved with a heuristic model, achieved a sufficient and satisfactory solution.
UR - http://www.scopus.com/inward/record.url?scp=85015175612&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-55209-5_6
DO - 10.1007/978-3-319-55209-5_6
M3 - Conference contribution
AN - SCOPUS:85015175612
SN - 9783319552088
T3 - Communications in Computer and Information Science
SP - 69
EP - 80
BT - Information Management and Big Data - 2nd Annual International Symposium, SIMBig 2015 and 3rd Annual International Symposium, SIMBig 2016, Revised Selected Papers
A2 - Lossio-Ventura, Juan Antonio
A2 - Alatrista-Salas, Hugo
PB - Springer Verlag
Y2 - 1 September 2016 through 3 September 2016
ER -
