Optimization of blood sample collection with timing and quality constraints

Amir Elalouf; Dmitry Tsadikovich; Sharon Hovav

doi:10.1111/itor.12354

Optimization of blood sample collection with timing and quality constraints

Amir Elalouf, Dmitry Tsadikovich, Sharon Hovav

Department of Management

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

17 Scopus citations

Abstract

We focus on planning transportation operations within a blood sample supply chain, which comprises clinics and a laboratory. Specifically, the main goal of this study is to obtain the optimal number of vehicles to be deployed and the scheduling of the pickup process. First, we formulate a mixed-integer programming (MIP) problem. Next, we develop a heuristic scheme composed of two heuristic algorithms and numerical search, and a new genetic algorithm. In an extensive numerical study, based on the data from a real-life blood sample collection process, we illustrate the potential of the new heuristic scheme.

Original language	English
Pages (from-to)	191-214
Number of pages	24
Journal	International Transactions in Operational Research
Volume	25
Issue number	1
DOIs	https://doi.org/10.1111/itor.12354
State	Published - Jan 2018

Bibliographical note

Publisher Copyright:
© 2016 The Authors. International Transactions in Operational Research © 2016 International Federation of Operational Research Societies

Funding

This work was supported by grant 135/2012 from the Israel National Institute for Health Policy Research.

Funders	Funder number
Israel National Institute for Health Policy Research

Keywords

MIP
blood samples collection
genetic algorithm
optimization
tabu search

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10.1111/itor.12354

Cite this

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Optimization of blood sample collection with timing and quality constraints

Abstract

Bibliographical note

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Keywords

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