Robust Wagner–Whitin algorithm with uncertain costs

In real-world applications, costs for products are not deterministic: neither static nor dynamic. They actually tend to be non-stationary and cross-correlated. To overcome this drawback, there have been some efforts by researchers to extend the Wagner–Whitin algorithm to consider stochastic costs. However, they assume that the information of probability density function of random costs exists. This paper applied a robust approach in reformulating the uncertain lot-sizing problem and used the Wagner–Whitin algorithm to find an optimal solution of its robust counterpart. The solution of the proposed algorithm in an example from the literature is compared with the classical one.