This study proposes improved parallel reactive hybrid particle swarm optimization (IPRHPSO) using an improved neighborhood schedule generation method for the integrated framework of optimal production scheduling and operational planning of an energy plant in a factory. Conventionally, in an energy plant, fixed loads of various tertiary energies have been utilized to solve the optimal operational planning of an energy plant so far. Additionally, in production lines, only the minimization of production time has been yet considered. Therefore, the secondary energy cost of a factory cannot be reduced accurately. However, in this study, the loads of various tertiary energies are calculated according to the candidates of production scheduling and the optimal operational planning of an energy plant is determined using the tertiary energies. This can explicitly reduce the secondary energy cost of a factory. The proposed method was applied to 10 jobs and machine JSPs each. Accordingly, it was verified that it can minimize the secondary energy cost and production time simultaneously, and realize fast computation through parallel computation using IPRHPSO.

中文翻译：

---

使用改进的邻域调度表生成方法的改进的并行反应混合粒子群优化算法，用于工厂中电厂的最佳生产调度和运营计划的集成框架

这项研究提出了一种改进的并行反应混合粒子群优化算法（IPRHPSO），它使用一种改进的邻域调度表生成方法，用于工厂中能源工厂的最佳生产调度和运营计划的集成框架。常规上，在能源工厂中，迄今为止，已经利用各种三次能源的固定负载来解决能源工厂的最佳运行计划。另外，在生产线中，仅考虑最小化生产时间。因此，工厂的二次能源成本无法准确降低。但是，在这项研究中，根据生产计划的候选者来计算各种三次能源的负荷，并使用三次能源来确定能源工厂的最佳运营计划。这可以显着降低工厂的二次能源成本。所提出的方法被应用于10个作业和每个机器JSP。因此，证实了它可以同时最小化二次能源成本和生产时间，并通过使用IPRHPSO的并行计算实现快速计算。