Improvement of Drug Delivery Routes Through the Adoption of Multi-Operator Evolutionary Algorithms and Intelligent Vans Capable of Reporting Real-Time Incidents

E. Onieva; E. Osaba; I. Angulo; A. Moreno; A. Bahillo; A. Perallos

doi:10.1109/TASE.2015.2476508

Improvement of Drug Delivery Routes Through the Adoption of Multi-Operator Evolutionary Algorithms and Intelligent Vans Capable of Reporting Real-Time Incidents

E. Onieva
, E. Osaba
, I. Angulo
, A. Moreno
, A. Bahillo
, A. Perallos

University of Deusto

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

An improved solution for drug distribution is presented in this paper. It is divided into two parts: I) a multi-operator evolutionary algorithm in charge of calculating the initial delivery routes and ii) an ambient intelligence-based support system able to tracing the merchandise along the distribution route. The first one establishes the routes to be followed by the vehicles, based on a proposal of estimation of the travel times. The second one is formed by a system able to recognize and trace the drugs inside each vehicle. A laboratory experimentation has been conducted in order to demonstrate the adequacy of the route calculator. In addition, a field experimentation has been carried out by implementing the traceability system in a delivery van which of the drug distributor in the city of Bilbao.

Original language	English
Pages (from-to)	1009-1019
Number of pages	11
Journal	IEEE Transactions on Automation Science and Engineering
Volume	14
Issue number	2
DOIs	https://doi.org/10.1109/TASE.2015.2476508
Publication status	Published - Apr 2017
Externally published	Yes

Keywords

combinatorial optimization
genetic algorithms
Intelligent transportation systems
mobile information systems
radio frequency identification (RFID)
supply chain management
traceability

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TASE.2015.2476508

Cite this

@article{9981c33a6b8142cc9399d56b334c5305,

title = "Improvement of Drug Delivery Routes Through the Adoption of Multi-Operator Evolutionary Algorithms and Intelligent Vans Capable of Reporting Real-Time Incidents",

abstract = "An improved solution for drug distribution is presented in this paper. It is divided into two parts: I) a multi-operator evolutionary algorithm in charge of calculating the initial delivery routes and ii) an ambient intelligence-based support system able to tracing the merchandise along the distribution route. The first one establishes the routes to be followed by the vehicles, based on a proposal of estimation of the travel times. The second one is formed by a system able to recognize and trace the drugs inside each vehicle. A laboratory experimentation has been conducted in order to demonstrate the adequacy of the route calculator. In addition, a field experimentation has been carried out by implementing the traceability system in a delivery van which of the drug distributor in the city of Bilbao.",

keywords = "combinatorial optimization, genetic algorithms, Intelligent transportation systems, mobile information systems, radio frequency identification (RFID), supply chain management, traceability",

author = "E. Onieva and E. Osaba and I. Angulo and A. Moreno and A. Bahillo and A. Perallos",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.",

year = "2017",

month = apr,

doi = "10.1109/TASE.2015.2476508",

language = "English",

volume = "14",

pages = "1009--1019",

journal = "IEEE Transactions on Automation Science and Engineering",

issn = "1545-5955",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "2",

}

Improvement of Drug Delivery Routes Through the Adoption of Multi-Operator Evolutionary Algorithms and Intelligent Vans Capable of Reporting Real-Time Incidents. / Onieva, E.; Osaba, E.; Angulo, I. et al.
In: IEEE Transactions on Automation Science and Engineering, Vol. 14, No. 2, 04.2017, p. 1009-1019.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Improvement of Drug Delivery Routes Through the Adoption of Multi-Operator Evolutionary Algorithms and Intelligent Vans Capable of Reporting Real-Time Incidents

AU - Onieva, E.

AU - Osaba, E.

AU - Angulo, I.

AU - Moreno, A.

AU - Bahillo, A.

AU - Perallos, A.

PY - 2017/4

Y1 - 2017/4

N2 - An improved solution for drug distribution is presented in this paper. It is divided into two parts: I) a multi-operator evolutionary algorithm in charge of calculating the initial delivery routes and ii) an ambient intelligence-based support system able to tracing the merchandise along the distribution route. The first one establishes the routes to be followed by the vehicles, based on a proposal of estimation of the travel times. The second one is formed by a system able to recognize and trace the drugs inside each vehicle. A laboratory experimentation has been conducted in order to demonstrate the adequacy of the route calculator. In addition, a field experimentation has been carried out by implementing the traceability system in a delivery van which of the drug distributor in the city of Bilbao.

AB - An improved solution for drug distribution is presented in this paper. It is divided into two parts: I) a multi-operator evolutionary algorithm in charge of calculating the initial delivery routes and ii) an ambient intelligence-based support system able to tracing the merchandise along the distribution route. The first one establishes the routes to be followed by the vehicles, based on a proposal of estimation of the travel times. The second one is formed by a system able to recognize and trace the drugs inside each vehicle. A laboratory experimentation has been conducted in order to demonstrate the adequacy of the route calculator. In addition, a field experimentation has been carried out by implementing the traceability system in a delivery van which of the drug distributor in the city of Bilbao.

KW - combinatorial optimization

KW - genetic algorithms

KW - Intelligent transportation systems

KW - mobile information systems

KW - radio frequency identification (RFID)

KW - supply chain management

KW - traceability

UR - https://www.scopus.com/pages/publications/85027560876

U2 - 10.1109/TASE.2015.2476508

DO - 10.1109/TASE.2015.2476508

M3 - Article

AN - SCOPUS:85027560876

SN - 1545-5955

VL - 14

SP - 1009

EP - 1019

JO - IEEE Transactions on Automation Science and Engineering

JF - IEEE Transactions on Automation Science and Engineering

IS - 2

ER -

Improvement of Drug Delivery Routes Through the Adoption of Multi-Operator Evolutionary Algorithms and Intelligent Vans Capable of Reporting Real-Time Incidents

Abstract

Keywords

UN SDGs

Access to Document

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