Consolidation strategies for the delivery of perishable products

• We study a freight consolidation problem for perishable products with stochastic demand.
• We propose a look-ahead heuristic that takes advantage of economies of scale by aiming to ship larger quantities.
• The heuristic’s annual cost is close to the optimal solution and requires significantly less computation time.
• The numerical results empirically show that a proportional cost allocation rule encourages cooperation among suppliers in the system.

A set of agricultural suppliers with low demands can save on long-haul transportation costs by consolidating their product. We consider a system with stochastic demand and a single consolidation point near the suppliers. We propose a look-ahead heuristic that takes advantage of economies of scale by aiming to ship larger quantities. We experimentally compare the heuristic’s performance against other simple policies, a rolling horizon algorithm, and a stochastic dynamic programming model. Our numerical results demonstrate that the heuristic provides solutions that are near the lower bound provided by the dynamic programming model, and that the benefits of consolidating depend on the size of the suppliers’ demand. We also propose a proportional cost allocation rule that encourages the suppliers to cooperate with each other instead of operating independently.