Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models

Abstract

Agri-food sector performance strongly impacts global economy, which means that developing optimisation models to support the decision-making process in agri-food supply chains (AFSC) is necessary. These models should contemplate AFSC’s inherent characteristics and sources of uncertainty to provide applicable and accurate solutions. To the best of our knowledge, there are no conceptual frameworks available to design AFSC through mathematical programming modelling while considering their inherent characteristics and sources of uncertainty, nor any there literature reviews that address such characteristics and uncertainty sources in existing AFSC design models. This paper aims to fill these gaps in the literature by proposing such a conceptual framework and state of the art. The framework can be used as a guide tool for both developing and analysing models based on mathematical programming to design AFSC. The implementation of the framework into the state of the art validates its. Finally, some literature gaps and future research lines were identified.

Keywords:

• agri-food supply chain
• design
• uncertainty
• conceptual framework
• literature review

Disclosure statement

No potential conflict of interest was reported by the authors.

Acknowledgements

The first author acknowledges the partial support of the Programme of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport (FPU15/03595), and the partial support of Project ‘Development of an integrated maturity model for agility, resilience and gender perspective in supply chains (MoMARGE). Application to the agricultural sector.’ Ref. GV/2017/025, funded by the Generalitat Valenciana. The other authors acknowledge the partial support of Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems, funded by the EU under its funding scheme H2020-MSCA-RISE-2015”.

Additional information

Funding

This first author was partially supported by the Programme of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport [grant number FPU15/03595]; the partial support of Project ‘Development of an integrated maturity model for agility, resilience and gender perspective in supply chains (MoMARGE). Application to the agricultural sector.’ Ref. GV/2017/025, funded by the Generalitat Valenciana. The other authors acknowledge the partial support of Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems, funded by the EU under its funding scheme H2020-MSCA-RISE-2015.