Solving the continuous flow-shop scheduling problem by metaheuristics

Abstract Continuous flow-shop scheduling problems circumscribe an important class of sequencing problems in the field of production planning. The problem considered here is to find a permutation of jobs to be processed sequentially on a number of machines under the restriction that the processing of each job has to be continuous with respect to the objective of minimizing the total processing time (flow-time). This problem is NP -hard. We consider the application of different kinds of metaheuristics from a practical point of view, examining the trade-off between running time and solution quality as well as the knowledge and efforts needed to implement and calibrate the algorithms. Computational results show that high quality results can be obtained in an efficient way by applying metaheuristics software components with neither the need to understand their inner working nor the necessity to manually tune parameters.

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