Applying genetic algorithms to a large-scale flow shop scheduling problem

In many large-scale manufacturing systems, the production scheduling relies heavily on heuristic algorithms. This investigation presents a novel genetic algorithm (GA) based scheduling mechanism to solve large-scale flow shop scheduling (FSS) problems. Introducing network structuring and forward calculation methods resulted in the mechanism. This mechanism contains the benefits of networked activities and can include not only a project but also a series of tasks. This mechanism simplifies FSS problems and is applicable in scheduling complicated flow shop processes. In the proposed approach, the mechanism and GA heuristics are developed separately, thus enhancing the performance of FSS by varying parameters or operator's setting within GA's heuristic and enables flexible modification of FSS application through altering scheduling criterion.