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.