The two stage assembly flowshop scheduling problem to minimize total tardiness

The two stage assembly flowshop scheduling problem has a lot of applications, and hence, it has recently received more attention in the scheduling literature. The performance measure of total tardiness is important as the fulfillment of due dates of customers has to be taken into account while making scheduling decisions. To the best of our knowledge, the problem with this performance measure has not been addressed so far, and hence, it is addressed in this paper. Different algorithms are proposed for the problem. The proposed algorithms are; an insertion algorithm, a genetic algorithm, two versions of simulated annealing algorithm (SA), and two versions of cloud theory-based SA. Moreover, the proposed insertion algorithm (PIA) is combined with the rest of the algorithms resulting in a total of eleven algorithms. Computational analysis, by using a non-parametric statistical test, indicates that one of the versions of the SA combined with the PIA performs better than the rest of the algorithms. The PIA helps in reducing the error of the SA by about seventy percent. It is worth to state that the performance of the combined algorithm is neither possible to achieve by the insertion algorithm alone nor by the simulated annealing alone no matter how much more computational time is given to the each.