A Robust Optimization Approach for the Resource Investment Problem of an Aircraft Final Assembly Line

In an aircraft final-assembly line (AFAL), test processes account for over 20% of all processes. And the processing times of test processes are usually uncertain owing to the fact that possible test failure brings about additional rounds of tests, which has a considerable impact on the resource investment of the AFAL. This paper studies a robust resource investment problem to minimize the resource investment cost for all realized processing times within budget uncertainty sets. A robust optimization model is formulated to determine the resource investment strategy. The robust model is reformulated and then solved by an exact solution approach based on an enhanced column and constraint generation algorithm featuring two novel acceleration techniques. Computational results demonstrate the effectiveness of our approach in solving realistic problem. Sensitivity analyses provide valuable managerial insights to real production. Note to Practitioners—The uncertainty of processing time has a considerable impact on the resource investment of the aircraft final-assembly line, since longer processing time incurs more resource investment than expected and consequently delay the whole assembly process. In this article, we present a robust model to deal with the uncertainty by finding an optimal robust resource investment strategy. The model that captures the characteristics of the real assembly line is computationally tractable and solved by an enhanced algorithm that is very efficient for practical application. The proposed approach allows the shop floor managers to make a satisfactory tradeoff between the total investment cost and the completion time, the total investment cost and the levels of robustness and uncertainty by adjusting the values of related parameters. In future, we will explore more effective algorithms for solving larger instances and consider other uncertainties like resource disruption.