An efficient population-based simulated annealing algorithm for the multi-product multi-retailer perishable inventory routing problem

• We considered a bi-level supply chain containing one manufacturer and several retailers that work under VMI system.
• We developed a new model for perishable inventory routing problem.
• We proposed an efficient population-based simulated annealing algorithm.
• Various upper and lower bounds are obtained.

This paper presents an inventory routing problem (IRP) involving perishable products with a fixed lifetime. It involves a multi-period multi-product IRP in two-level supply chains, where products are produced and delivered from a single manufacturer to several retailers utilizing multiple shipping strategies through a fleet of appropriately capacitated vehicles. The goal is to minimize total cost while ensuring that no stock out occurs. A mathematical model is presented. A population-based simulated annealing (PBSA) algorithm is proposed. This PBSA algorithm is compared with simulated annealing (SA) and genetic algorithms (GA) which shows the superiority of the PBSA algorithm. CPLEX solver, branch-and-cut method, and different relaxation methods also were used, so as to obtain upper and lower bounds. The computational experiments show the high efficiency of the PBSA algorithm.