The energy consumption loss is high particularly in manufacturing processes involving heating furnaces. Moreover, the mandatory constraints in continuous heating stage bring difficult challenges to production scheduling. To improve the production efficiency and reduce the energy consumption in a hybrid flow shop with continuous and discrete processing stages, this study developed an adaptive selection multi-objective optimization algorithm with preference (ASMOAP). The mandatory constraints of continuous processing stage are transformed into one of the optimization objectives, which is defined as maximum excess value of adjustment time in this paper. A multi-objective optimization scheduling model with the makespan, energy consumption, and maximum excess of adjustment time is established. The optimization preference is designed in the proposed multi-objective optimization algorithm. The maximum excess of adjustment time is set as the multi-objective optimization preference. Three adaptive selection strategies are designed for the algorithm based on the proportions of outstanding and preference individuals to eliminate constraint conflicts. Presented results prove that the proposed algorithm could effectively solve hybrid flow shop scheduling problem considering discrete and continuous processing stages with limited time. It can be applied to obtain a better feasible solution while improving the efficiency and reducing the energy consumed in practical production processes.

特别是在涉及加热炉的制造过程中，能耗损失很高。此外，连续加热阶段的强制性约束给生产调度带来了严峻的挑战。为了提高具有连续和离散加工阶段的混合流水线车间的生产效率并降低能耗，本研究开发了一种具有偏好的自适应选择多目标优化算法（ASMOAP）。将连续加工阶段的强制约束转化为优化目标之一，本文将其定义为调整时间的最大超额值。建立了工期、能耗和最大调整时间超限的多目标优化调度模型。在所提出的多目标优化算法中设计了优化偏好。调整时间的最大超出设置为多目标优化偏好。该算法根据优秀个体和偏好个体的比例设计了三种自适应选择策略，以消除约束冲突。所提出的结果证明，所提出的算法可以有效地解决考虑离散和连续处理阶段的混合流水车间调度问题，时间有限。在实际生产过程中，在提高效率、降低能耗的同时，可以得到更好的可行方案。该算法根据优秀个体和偏好个体的比例设计了三种自适应选择策略，以消除约束冲突。所提出的结果证明，所提出的算法可以有效地解决考虑离散和连续处理阶段的混合流水车间调度问题，时间有限。在实际生产过程中，在提高效率、降低能耗的同时，可以得到更好的可行方案。该算法根据优秀个体和偏好个体的比例设计了三种自适应选择策略，以消除约束冲突。所提出的结果证明，所提出的算法可以有效地解决考虑离散和连续处理阶段的混合流水车间调度问题，时间有限。在实际生产过程中，在提高效率、降低能耗的同时，可以得到更好的可行方案。