A Branch-and-price Algorithm for Parallel Machine Campaign Planning under Sequence Dependent Family Setups and Co-Production

We investigate a tactical level production planning problem in process industries under costly sequence dependent family setups, which drives the need for manufacturing of product families in campaigns. The motivation of our work is float glass manufacturing, which has some unique properties such as co-production and uninterruptible production. To solve the problem, we develop a branch-and-price algorithm based on a novel formulation of the problem. Our algorithm is capable of providing consistent performance in different problem sizes. We compare our proposed algorithm with previous work on the same problem by running computational experiments.