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Dear XX:
The reviewers have commented on your above paper. They indicated that it is not acceptable for publication in its present form.
However, if you feel that you can suitably address the reviewers' comments (included below), I invite you to revise and resubmit your manuscript.
Please carefully address the issues raised in the comments.

Reviewer #1: This paper discuss flexible job-shop scheduling problem with random machine breakdowns, and a knowledge-based multi-objective evolutionary algorithm (KBMOEA) was developed to deal with the probelem. The authers proposed a knowledge-based heuristic searching architecture and NSGA-II was employed to perform the searching task. In the experimental results, the algorithm was compared with many well-known heuristics and performed better than other methods. But the results didn't present the convergency and the computing time of this algorithm compare with other methods. In addition, the contribution of the paper should be explained early in the paper.

This paper focuses on robust solutions to the flexible job shop scheduling problem with random machine breakdowns. Two surrogate measures are proposed to describe the level of robustness for a given schedule. A bi-objective optimization problem is constructed by incorporating makespan and robustness, and then a knowledge-based MOEA is applied to solve the problem. Computational results show that the proposed surrogate measures are effective.
>
> The topic of the paper is interesting, but an extensive revision is needed to make it publishable.
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