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Sustainability in Production Systems: A Review of Optimization Methods Studying Social Responsibility Issues in Workforce Scheduling

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Service Orientation in Holonic and Multi-Agent Manufacturing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 640))

Abstract

Production scheduling in manufacturing systems is a highly complex task. It involves the allocation of limited resources (machines, tools, personnel, etc.) for the execution of specific jobs. In the case of workforce scheduling, unique human characteristics must also be considered, further complicating the task, as similar characteristics are not present in machines. Numerous published research works have examined issues of workforce scheduling by evaluating employee characteristics. Moreover, as business policies must nowadays sup-port social responsibility objectives, academic works have considered this dimension. This paper reviews academic literature on workforce scheduling strategies that consider social responsibility issues in order to identify quantitative methods and techniques employed. A systematic literature review is conducted to form an objective, rigorous, and reproducible framework that minimizes biases in the inclusion/exclusion of analysed works. Applications, trends, and gaps are identified, thus identifying pertinent avenues for future research.

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Acknowledgment

The work presented in this paper was supported under a postgraduate scholarship awarded to the first author by Universidad de La Sabana.

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Correspondence to Jairo R. Montoya-Torres .

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Moreno-Camacho, C.A., Montoya-Torres, J.R. (2016). Sustainability in Production Systems: A Review of Optimization Methods Studying Social Responsibility Issues in Workforce Scheduling. In: Borangiu, T., Trentesaux, D., Thomas, A., McFarlane, D. (eds) Service Orientation in Holonic and Multi-Agent Manufacturing. Studies in Computational Intelligence, vol 640. Springer, Cham. https://doi.org/10.1007/978-3-319-30337-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-30337-6_11

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