A genetic algorithm for the vendor-managed inventory routing problem with lost sales

• A genetic algorithm is proposed for vendor-managed inventory routing problems with lost sales.
• The proposed genetic algorithm demonstrates the excellent performance.
• The solution quality of the proposed genetic algorithm is affected by some problem parameters.
• The resource capacity should be considered as decision variables to optimize the system operation.

This paper proposes a genetic algorithm (GA) for the inventory routing problem with lost sales under a vendor-managed inventory strategy in a two-echelon supply chain comprised of a single manufacturer and multiple retailers. The proposed GA is inspired by the solving mechanism of CPLEX for the optimization model of the problem. The proposed GA determines replenishment times and quantities and vehicle routes in a decoupled manner, while maximizing supply chain profits. The proposed GA is compared with the optimization model with respect to the effectiveness and efficiency in various test problems. The proposed GA finds solutions in a short computational time that are very close to those obtained with the optimization model for small problems and solutions that are within 3.2% of those for large problems. Furthermore, sensitivity analysis is conducted to investigate the effects of several problem parameters on the performance of the proposed GA and total profits.