Multi-objective scenario optimization of the food supply chain – Slovenian case study

Drofenik, Jan; Pahor, Bojan; Kravanja, Zdravko; Pintarič, Zorka Novak

doi:10.1016/j.compchemeng.2023.108197

Cited by 8 publications

(1 citation statement)

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“…The supply of water to the industry is being threatened by the current state of global water availability (Sa’ad et al 2021 ). Due to threats of water scarcity on socio-economic development (Liu et al 2017 ), there is a need to assess the trade-off between production and environmental impact (Drofenik et al 2021 ). Water scarcity limits the growth of water-intensive industries (You et al 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Cost and water footprint trade-off in a supply chain optimization model

Cruz

Tan

2023

Clean Techn Environ Policy

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Water footprint (WF) is an appropriate tool to help any water-intensive industrial system to adapt to climate change. WF is a metric where the direct and indirect freshwater consumption of a country, firm, activity, or product are quantified. Most of existing WF literature emphasizes the assessment of products, not the optimal decision making in the supply chain. To address this research gap, a bi-objective optimization model is developed for supplier selection in a supply chain that minimizes costs and WF. Apart from determining the sources of raw materials to use in producing the products, the model also determines the actions to be taken by the firm in case of supply shortages. The model is demonstrated using three illustrative case studies which show that WF embedded in the raw materials can influence the actions to be taken when addressing issues on raw material availability. The WF becomes significant in the decisions in this bi-objective optimization problem when it is given a weight of at least 20% (or the weight of the cost is at most 80%) for case study 1 and at least 50% for case study 2. When the assigned weight in cost reaches the point where WF becomes significant, the increase in the assigned weight in WF has an inverse impact on the total cost. Case study 3 demonstrates the stochastic variant of the model. Graphical abstract Supplementary Information The online version contains supplementary material available at 10.1007/s10098-023-02549-5.

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Section: Introductionmentioning

confidence: 99%