Wang Wenjie, Tian Guangdong, Zhang Honghao, Xu Kangkang, Miao Zheng
Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Ministry of Education), National Demonstration Center for Experimental Mechanical Engineering Education School of Mechanical Engineering, Shandong University, Jinan, 250061, People's Republic of China.
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, 150001, People's Republic of China.
Environ Sci Pollut Res Int. 2021 Nov 12. doi: 10.1007/s11356-021-17292-x.
As one of the mainstream development directions of remanufacturing industry, remanufacturing system scheduling has become a hot research topic recently. This study regards a scheduling problem for remanufacturing systems where end-of-life (EOL) products are firstly disassembled into their constituent components, and next these components are reprocessed to like-new states. At last, the reprocessed components are reassembled into new remanufactured products. Among various system configurations, we investigate a scheduling problem for the one with parallel disassembly workstations, several parallel flow-shop-type reprocessing lines and parallel reassembly workstations for the objective of minimize total energy consumption. To address this problem, a mathematical model is established and an improved genetic algorithm (IMGA) is proposed to solve it due to the problem complexity. The proposed IMGA adopts a hybrid initialization method to improve the solution quality and diversity at the beginning. Crossover operation and mutation operation are specially designed subject to the characteristics of the optimization problem. Besides, an elite strategy is combined to gain a faster convergence speed. Numerical experiments are conducted and the results verify the effectiveness of the scheduling model and proposed algorithm. The work can assist production managers in better planning a scheduling scheme for remanufacturing systems.
作为再制造产业的主流发展方向之一，再制造系统调度近来已成为一个热门研究课题。本研究关注再制造系统的一种调度问题，在此问题中，报废（EOL）产品首先被拆解成其组成部件，接着这些部件被再加工至全新状态。最后，再加工后的部件被重新组装成新的再制造产品。在各种系统配置中，我们针对具有并行拆解工作站、若干并行流水车间型再加工生产线以及并行组装工作站的系统，研究其调度问题，目标是使总能耗最小化。为解决此问题，鉴于问题的复杂性，建立了一个数学模型并提出一种改进遗传算法（IMGA）来求解。所提出的IMGA在初始阶段采用混合初始化方法来提高解的质量和多样性。交叉操作和变异操作根据优化问题的特点进行了专门设计。此外，结合了精英策略以获得更快的收敛速度。进行了数值实验，结果验证了调度模型和所提算法的有效性。这项工作可协助生产经理更好地规划再制造系统的调度方案。
