In recent years, sustainable development and green manufacturing have attracted widespread attention to environmental problems becoming increasingly serious. Meanwhile, affected by the intensification of market competition and economic globalization, distributed manufacturing systems have become increasingly common. This paper addresses the energy-efficient scheduling of the distributed permutation flowshop (EEDPFSP) with the criteria of minimizing both total flow time and total energy consumption. Considering the distributed and multi-objective optimization complexity, an improved NSGAII algorithm (INSGAII) is proposed. First, we analyze the problem-specific characteristics and designed new operators based on the knowledge of the problem. Second, four constructive heuristic algorithms are proposed to produce high-quality initial solutions. Third, inspired by the artificial bee colony algorithm, we propose a new colony generation method using the operators designed. Fourth, a local intensification is designed for exploiting better non-dominated solutions. The influence of parameter settings is investigated by experiments to determine the optimal parameter configuration of the INSGAII. Finally, a large number of computational tests and comparisons have been carried out to verify the effectiveness of the proposed INSGAII in solving EEDPFSP.

近年来，环境问题日益严重，可持续发展和绿色制造引起了广泛关注。同时，受市场竞争加剧和经济全球化的影响，分布式制造系统越来越普遍。本文以最小化总流动时间和总能耗为标准，讨论了分布式置换流水车间 (EEDPFSP) 的节能调度问题。考虑到分布式和多目标优化的复杂性，提出了一种改进的NSGAII算法（INSGAII）。首先，我们分析问题的具体特征，并根据问题的知识设计新的算子。其次，提出了四种构造启发式算法来产生高质量的初始解决方案。第三，受人工蜂群算法的启发，我们使用设计的算子提出了一种新的蜂群生成方法。第四，局部集约化旨在开发更好的非支配解决方案。通过实验研究参数设置的影响，以确定 INSGAII 的最佳参数配置。最后，进行了大量的计算测试和比较，以验证所提出的 INSGAII 在解决 EEDPFSP 中的有效性。