In this paper, a multi-objective hybrid flowshop rescheduling problem (HFRP) is addressed in a dynamic shop environment where two types of real-time events, namely machine breakdown and job cancellation, simultaneously happen. For the addressed problem, two objectives are considered. One objective concerning the production efficiency is minimizing the maximum completion time or makespan, while regarding with the instability, the total number of the jobs assigned to different machines between the revised and the origin schedule is considered. A multi-objective evolutionary algorithm based on decomposition (MOEA/D) is applied to solve this problem. In the algorithm, the weighted sum approach is used as the decomposition strategy. The algorithm is, then, rigorously compared with three state-of-the-art evolutionary multi-objective optimizers, and the computational results demonstrate the effectiveness and efficiency of the algorithm.

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