Flow Shop Scheduling Problem with Missing Operations: Genetic Algorithm and Tabu Search

Flow shop scheduling problem with missing operations is studied in this paper. Missing operations assumption refers to the fact that at least one job does not visit one machine in the production process. A mixed-binary integer programming model has been presented for this problem to minimize the makespan. The genetic algorithm (GA) and tabu search (TS) are used to deal with the optimization problem. According to computational experiments on data sets, it is suggested that GA is a more appropriate method to solve this problem. GA can reach good-quality solutions in short computational time, and can be used to solve large scale problems effectively.