A Product-Design-Change-Based Recovery Control Algorithm for Supply Chain Disruption Problem

In very recent years, large-scale disruptions brought by major global and local emergencies have posed many challenges with respect to the recovery control of supply chain systems. This work investigates a problem regarding the optimal control of a supply chain by considering product design change in order to enable manufacturers to recover their disrupted supply chain quickly. A two-layer optimization model is developed, in which the lower model is used to optimize the product design change path, and the upper model is used to select the appropriate alternative suppliers and schedule the delivery of customer orders. To solve the developed model, a hybrid ant colony optimization (HACO) algorithm is designed, which is combined with a Gurobi solver and uses some special strategies. The validity of the proposed algorithm is illustrated experimentally through computational tests and systematic comparison with the existing methods. It is reported that the losses caused by supply chain disruptions are reduced significantly. The proposed model and algorithm can provide a potentially useful tool that can help manufacturers decide upon the optimal form of recovery control when a supply chain system experiences a massive supply disruption.