Abstract
Increased food availability to fulfil current and future demand may arise from efficient supply chain networks. Lack of cold-chain infrastructure leads to food loss, environmental degradation, and social injustice (e.g., food poverty, farmer
fairness). A well-organized logistics system is critical for accommodating optimal production and distribution while minimising post-harvest losses and reducing social and environmental impacts. The aim of this research is to present a conceptual multiagent simulation model to aid policy making in sustainable cold chain operations and logistics management.
A cold supply chain model and its conceptual multiagent simulation design are presented in this research. A case study of a Scottish salmon is used to demonstrate the simulation design. The model focuses on operations and
logistics, with the goal of optimising resource utilisation and product quality delivery. Several agents representing real stakeholders are modelled at different levels of the system. The conceptual design of the multiagent simulation is
discussed and presented using the Capacity, Roles, Interaction and Organisation (CRIO) meta model approach, where groups and roles are the main entities.
The first mile logistics infrastructure focus and the farmers-processors-wholesalers (suppliers) cooperation concepts are introduced. The distribution of cold chain products from suppliers to the retailers/consumers is also considered
throughout the chain in order to conceptualise decision making process in Agent Based Modelling (ABM) settings.
The fully implemented model will be able to consider complete sustainability dimensions: environment (green logistics), economy (efficiency and affordability), and social (fairness to farmer and food loss reduction). The complete model may be utilised by key stakeholders to evaluate Cold chain interventions without requiring real world testing, hence reducing risk. Effective cold storage and cold transport (supply and distribution) may lead to reduce food losses and facilitates access to more lucrative markets.
When completely implemented, the model can aid in the development of a comprehensive road map that will allow the food cold chain industry to discover emission-cutting as well as social and economic benefits. As a result, it may assist cold chain stakeholders in meeting the UK’s net zero 2050 target, guarantying food security and affordability for UK consumers, and boosting economic potential for the UK food industry.
fairness). A well-organized logistics system is critical for accommodating optimal production and distribution while minimising post-harvest losses and reducing social and environmental impacts. The aim of this research is to present a conceptual multiagent simulation model to aid policy making in sustainable cold chain operations and logistics management.
A cold supply chain model and its conceptual multiagent simulation design are presented in this research. A case study of a Scottish salmon is used to demonstrate the simulation design. The model focuses on operations and
logistics, with the goal of optimising resource utilisation and product quality delivery. Several agents representing real stakeholders are modelled at different levels of the system. The conceptual design of the multiagent simulation is
discussed and presented using the Capacity, Roles, Interaction and Organisation (CRIO) meta model approach, where groups and roles are the main entities.
The first mile logistics infrastructure focus and the farmers-processors-wholesalers (suppliers) cooperation concepts are introduced. The distribution of cold chain products from suppliers to the retailers/consumers is also considered
throughout the chain in order to conceptualise decision making process in Agent Based Modelling (ABM) settings.
The fully implemented model will be able to consider complete sustainability dimensions: environment (green logistics), economy (efficiency and affordability), and social (fairness to farmer and food loss reduction). The complete model may be utilised by key stakeholders to evaluate Cold chain interventions without requiring real world testing, hence reducing risk. Effective cold storage and cold transport (supply and distribution) may lead to reduce food losses and facilitates access to more lucrative markets.
When completely implemented, the model can aid in the development of a comprehensive road map that will allow the food cold chain industry to discover emission-cutting as well as social and economic benefits. As a result, it may assist cold chain stakeholders in meeting the UK’s net zero 2050 target, guarantying food security and affordability for UK consumers, and boosting economic potential for the UK food industry.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 26th Annual Conference of Logistics Research Network (LRN) |
| Publisher | The Chartered Institute of Logistics and Transport |
| Pages | 328-335 |
| Number of pages | 8 |
| ISBN (Print) | 9781904564690 |
| Publication status | Published - 7 Sept 2022 |
| Event | 26th Annual Conference of The Chartered Institute of Logistics and Transport, Logistics Research Network - Birmingham, United Kingdom Duration: 7 Sept 2022 → 9 Sept 2022 |
Conference
| Conference | 26th Annual Conference of The Chartered Institute of Logistics and Transport, Logistics Research Network |
|---|---|
| Country/Territory | United Kingdom |
| City | Birmingham |
| Period | 7/09/22 → 9/09/22 |
Keywords
- Cold chain
- Salmon supply chain
- First mile logistics
- Transportation distribution
- Agent-based modeling
