Abstract We propose an enhanced multi-objective harmony search (EMOHS) algorithm and a Gaussian mutation to solve the flexible flow shop scheduling problems with sequence-based setup time, transportation time, and probable rework. A constructive heuristic is used to generate the initial solution, and clustering is applied to improve the solution. The proposed algorithm uses response surface methodology to minimize both maximum completion time and mean tardiness, concurrently. We evaluate the efficacy of the proposed algorithm using computational experiments based on five measures of diversity metric, simultaneous rate of achievement for two objectives, mean ideal distance, quality metric, and coverage. The experimental results demonstrate the effectiveness of the proposed EMOHS compared with the existing algorithms for solving multi-objective problems.

中文翻译：

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一种求解带有返工和运输的柔性流水车间调度问题的仿真优化模型

摘要 我们提出了一种增强的多目标和声搜索 (EMOHS) 算法和高斯变异，以解决具有基于序列的设置时间、运输时间和可能返工的灵活流水车间调度问题。使用建设性启发式方法生成初始解决方案，并应用聚类来改进解决方案。所提出的算法使用响应面方法来同时最小化最大完成时间和平均延迟。我们使用基于多样性度量、两个目标的同时实现率、平均理想距离、质量度量和覆盖率的五个度量的计算实验来评估所提出算法的有效性。