Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model

Abstract

Lack of homogeneity in the product (LHP) appears in some production processes that confer heterogeneity in the characteristics of the products obtained. Supply chains with this issue have to classify the product in different homogeneous subsets, whose quantity is uncertain during the production planning process. This paper proposes a generic framework for reviewing in a unified way the literature about production planning models dealing with LHP uncertainty. This analysis allows the identification of similarities among sectors to transfer solutions between them and gaps existing in the literature for further research. The results of the review show: (1) sectors affected by LHP inherent uncertainty, (2) the inherent LHP uncertainty types modelled, and (3) the approaches for modelling LHP uncertainty most widely employed. Finally, we suggest a conceptual model reflecting the aspects to be considered when modelling the production planning in sectors with LHP in an uncertain environment.

KEYWORDS:

• Planning
• optimisation
• production
• uncertainty
• mathematical modelling

Acknowledgments

We would like to thank you to the three anonymous reviewers and the editor all their suggestions, that have undoubtedly improved the original version of the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was initiated within the framework of the project funded by the Ministerio de Economía y Competitividad [Ref. DPI2011-23597] entitled ‘Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity’ (PLANGES-FHP) already finished. After, the project leading to this application has received funding  from the European Union’s research and innovation programme under the  H2020 Marie Skłodowska-Curie Actions with the grant agreement No  691249, Project entitled 'Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems' (RUC-APS).