A climate driven decision-support model for the distribution of perishable products, 2017

see the paper (free-access) till sept.2017



• This paper addresses an open field of research in the supply chain of perishable products.
• This paper provides a MILP model for the planning of processing and distribution operations in cold chains.
• This paper incorporates the interactions of distribution constraints and climate conditions.
• This paper illustrates a case study to demonstrate the influence of climate on the cold chain costs.
• This paper leads to the reduction of the energy consumption for cold chain operations.


The cold chains prevent perishable products from decay, but are highly energy-intensive. As much as 15% of total worldwide energy already fuels cold chains infrastructures and since 40% of food deliveries would need refrigeration, the growth of global food demand and of the widening of the global supply chains will enormously increase the energy request and the associated carbon emissions. The environmental temperature has indeed a clear effect on the performance of the cold chain, and the interaction between climate and the distribution of perishable products cannot be ignored. In this paper a mixed-integer linear programming model for the planning of the production, storage and distribution operations of perishable products which incorporates the interactions with the weather conditions is formulated. This addresses an open field of research, which is still uncovered. The proposed model has been applied to an illustrative case study of a cold chain for cherries, that demonstrates the influence of the weather conditions on the energy costs for the products refrigeration on vehicles during transportation and at the warehouse during storage. Successful control of the distribution operations according to the weather conditions can result in significant reduction of energy consumption and costs, which increase indeed with the raise of environmental temperatures and stresses. Based on the results obtained in this study, these costs are not handled by the extant operations planning models, and their minimization can lead to significant economic and environmental savings for the cold chain.


  • Cold chain;
  • Perishable;
  • Transport;
  • Optimization;
  • Climate;
  • Energy