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Title: Modelling human network behaviour using simulation and optimization tools: the need for hybridization
Author: Gruler, Aljoscha
Armas Adrián, Jésica de
Juan Pérez, Ángel Alejandro
Goldsman, David
Others: Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Universitat Pompeu Fabra
Georgia Institute of Technology
Keywords: modelling human behaviour
human networks
Issue Date: Jan-2020
Publisher: SORT: Statistics and Operations Research Transaction
Citation: Gruler, A., Armas, J., Juan, A.A. & Goldsman, D. (2019). Modelling human network behaviour using simulation and optimization tools: the need for hybridization. SORT: Statistics and Operations Research Transactions, 43(2), 193-222. doi: 10.2436/20.8080.02.85
Project identifier: info:eu-repo/grantAgreement/2018-1-ES01-KA103-049767
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Abstract: The inclusion of stakeholder behaviour in Operations Research / Industrial Engineering (OR/IE) models has gained much attention in recent years. Behavioural and cognitive traits of people and groups have been integrated in simulation models (mainly through agent-based approaches) as well as in optimization algorithms. However, especially the influence of relations between different actors in human networks is a broad and interdisciplinary topic that has not yet been fully investigated. This paper analyses, from an OR/IE point of view, the existing literature on behaviour-related factors in human networks. This review covers different application fields, including: supply chain management, public policies in emergency situations, and Internet-based human networks. The review reveals that the methodological approach of choice (either simulation or optimization) is highly dependent on the application area. However, an integrated approach combining simulation and optimization is rarely used. Thus, the paper proposes the hybridization of simulation with optimization as one of the best strategies to incorporate human behaviour in human networks and the resulting uncertainty, randomness, and dynamism in related OR/IE models.
Language: English
ISSN: 1696-2281MIAR

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