A robust optimization approach for repairing and overhauling in a captive repair shop under uncertainty

A robust optimization model is a paradigm for decision-making under uncertainty, where the parameters are given in the form of uncertainty sets. In this paper, we establish a robust optimization model for a captive repair shop. This paper is divided into two parts. In the first part, we present an uncertain linear optimization model involving the product of two uncertain parameters. Information associated with these uncertain parameters are modelled in the form of polyhedral and ellipsoidal uncertainty sets. The max-min regret approach is applied to solve the uncertain optimization model. In the second part, the robust optimization technique is applied to a multi-plant captive repair shop for repairing and overhauling multiple products over multiple periods. Numerical examples are presented to illustrate the theoretical results.