Scheduling the two-machine flowshop to hedge against processing time uncertainty

This paper addresses the two‐machine flowshop scheduling problem with uncertain job processing times. It is assumed that in the realization of a schedule, job processing times may take any values from their corresponding intervals given before scheduling. The objective is to determine a robust schedule with the minimum makespan of the restricted worst‐case scenario among all possible scenarios to hedge against processing time uncertainty for a given number of jobs. We formulate the problem of interest as a robust counterpart optimization model, and apply a simulated annealing (SA) algorithm and an iterated greedy (IG) algorithm to solve it. The experimental results show that both algorithms are effective in determining robust schedules for small‐size problems, while the IG algorithm is more effective than the SA algorithm for large‐size problems, albeit at the expense of more computational time.