In this paper we present SS-GNEH, a simulation-based algorithm for the
Permutation Flowshop Sequencing Problem (PFSP). Given a PFSP instance, the SSGNEH
algorithm incorporates a randomness criterion to the classical NEH heuristic
and starts an iterative process in order to obtain a set of alternative solutions, each of
which outperforms the NEH algorithm. Thus, a random but oriented local search of
the space of solutions is performed, and a list of "good alternative solutions" is
obtained. We can then consider several desired properties per solution other than
maximum time employed, such as balanced idle times among machines, number of
completed jobs at a given target time, etc. This allows the decision-maker to
consider multiple solution characteristics other than just those defined by the
aprioristic objective function. Therefore, our methodology provides flexibility
during the sequence selection process, which may help to improve the scheduling
process. Several tests have been performed to discuss the effectiveness of this
approach. The results obtained so far are promising enough to encourage further
developments on the algorithm and its applications in real-life scenariosPostprint (published version
