Robust and stable scheduling for FJSP under random machine breakdown by use of genetic algorithm and simulation

Current research addresses finding robust and stable schedule for the flexible job shop problem under machine breakdown. We have used simulation to investigate the effect of machine breakdown. Two-stage of metaheuristic algorithm is developed to generate robust and stable schedule and is integrated with simulation algorithm. Because makespan is primitive objective of every scheduling problem, in the first stage of integrated algorithm, makespan is improved and in the second stage linear combination of stability, robustness and makespan is proposed. In our proposed model we provide condition that scheduler can decide which objective is important than the others, then scheduling scheme can be generated based on this decision. In the second stage, we have investigated four type of coefficient in combination cost function, and our experiment shows that it is possible to achieve high stability and robustness measures without sacrificing much from the makespan level. Genetic and differential evolution algorithms are used in proposed model then a statistical hypothesis test is conducted to compare the performance of them.

Abstract licence: CC BY-NC

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