An Effective Hybrid Differential Evolution Algorithm Incorporating Simulated Annealing for Joint Replenishment and Delivery Problem with Trade Credit

In practice, suppliers often provide retailers with forward financing to increase demand or decrease inventory. This paper proposes a new and practical joint replenishment and delivery (JRD) model by considering trade credit. However, because of the complex mathematical properties of JRD, high-quality solutions to the problem have eluded researchers. We design an effective hybrid differential evolution algorithm based on simulated annealing (HDE-SA) that can resolve this non-deterministic polynomial hard problem in a robust and precise way. After determining the suitable parameters by a parameter-tuning test, we verify the performance of the HDE-SA through numerical JRD examples. Compared with the results of other popular evolutionary algorithms, results of randomly generated JRDs indicate that HDE-SA can always obtain slightly lower total costs than differential evolution algorithm (DE) and genetic algorithm (GA) under different situations. Moreover, the convergence rate of the HDESA is higher than that of DE and GA. Thus, the proposed HDE-SA is a potential tool for the JRD with trade credit.