An evolutionary algorithm for the permutation flowshop scheduling problem with total tardiness criterion

The permutation flowshop scheduling problem (PFSP) has been studied by many researchers. It has been addressed using various approaches, including branch and bound, tabu search, simulated annealing and genetic algorithms. This study presents a new evolutionary algorithm approach to the PFSP with a total tardiness criterion that is not only easy to tune and quite simple but also effective. The algorithm includes additional techniques, such as a mating procedure specifically designed for the problem, a local search with two different neighbourhood sizes, and a revision procedure. The algorithm was tested against 540 benchmark problems that have already been used to test the state‐of‐the‐art approaches. The results show that our algorithm's effectiveness increases as the problem size grows.