Report on findings on transportation and logistics of selected food value chains:Salmon to fillet case study

• Main Authors: Aditjandra, Paulus, De, Arijit, Gorton, Matthew, Hubbard, Carmen, Pang, Gu, Mehta, Shraddha, Thakur, Maitri, Richardsen, Roger, Bogason, Sigurdur, Olafsdottir, Gudrun
• Format: Book
• Language: English
• Published: 2019
• Subjects: Atlantic salmon
• Online Access: https://research.manchester.ac.uk/en/publications/591ddf21-5df0-426b-9ac9-48c26dc361cb; https://doi.org/10.5281/zenodo.5105433; https://pure.manchester.ac.uk/ws/files/277417107/FINAL_FOR_WEB.pdf; https://zenodo.org/record/5105433

Transportation has significant impact on food costs and the environment. It is a major contributor to carbon emissions, accounting for almost a quarter of the CO2 emissions in the EU, of which 30% is attributed to the food sector. This deliverable addresses the modelling of food chains’ transportation and logistics. It develops a robust model for policy support, which is applied to a specific case as a worked example. The approach can be used to model the transport and logistics of other food supply chains, given data availability. The mathematical modelling aims to optimise the cost and effectiveness of logistics operations. It also allows for the integration and consideration of environmental aspects within transportation, processing and distribution operations. Specifically, the deliverable focuses on the development of a logistics mathematical model using Atlantic salmon as an exemplary example of a globally integrated food supply chain. A Norwegian salmon exporter was engaged to supply data for validating the mathematical model. The model follows a multi-objective optimization approach that captures the trade-off between total logistics cost and the environment. It has two objectives. Firstly, to minimize total costs associated with transportation, fuel consumption, inventory holding, processing and residuals/waste. Secondly, to reduce CO2 emissions incurred by production at plants, transportation from suppliers to plants, and transportation from plants to customers. Constraints related to supply, processing capacity, storage capacity, demand, carbon emissions, inventory balancing, transportation capacity, and different modes of transportation between different types of plants and facilities are also consider within the model. Model development, validation and policy recommendation occurred in four stages: (i) mapping supply chain linkages and product flows, (ii) designing the mathematical model, (iii) data collection for parameters of the model and (iv) model validation and deriving policy recommendation. ...