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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 16/2020

17.07.2019 | Real-world Optimization Problems and Meta-heuristics

Modeling and optimization of a reliable blood supply chain network in crisis considering blood compatibility using MOGWO

verfasst von: Seyed Behzad Ghorashi, Maryam Hamedi, Ramin Sadeghian

Erschienen in: Neural Computing and Applications | Ausgabe 16/2020

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Abstract

Due to the prominent role of blood in human life, designing an efficient blood supply chain in case of an emergency situation is essential especially considering blood compatibility. This research proposes a multi-objective model for emergency blood supply chain management considering blood compatibility, routing, and location–allocation decisions. The blood supply chain network consists of donors, collection facilities, laboratories, blood centers, and hospitals. The mathematical model aims to minimize total supply chain cost and time while maximizing minimum reliability of established routes by making decisions regarding location–allocation, blood flow, inventory levels, and optimal routes. In order to solve the problem, a novel algorithm called Multi-Objective Grey Wolf Optimizer is used and compared to two classical algorithms Multi-Objective Particle Swarm Optimization and Non-dominated Sorting Genetic Algorithm-II. Performance of the algorithms is evaluated in various test problems using powerful measures. Also, the application of the proposed model is investigated in a case study in Iran’s capital, Tehran. Based on the results, important managerial insights are derived and optimal locations for facilities, inventory levels, routes and blood flow between facilities are determined.
Vorheriger Artikel Evolutionary model construction for electricity consumption prediction
Nächster Artikel Feature selection using binary grey wolf optimizer with elite-based crossover for Arabic text classification

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Metadaten
Titel
Modeling and optimization of a reliable blood supply chain network in crisis considering blood compatibility using MOGWO
verfasst von
Seyed Behzad Ghorashi
Maryam Hamedi
Ramin Sadeghian
Publikationsdatum
17.07.2019
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 16/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-019-04343-1

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