Dual-service integrated scheduling of manufacturing and logistics for multiple tasks in cloud manufacturing

To meet the frequent transportation requirements between distributed manufacturing services (MSs), logistics services (LSs) have played an essential role in cloud manufacturing. However, previous studies on service scheduling focused on MSs and simply treated the logistics process as a linear relationship with distance. In fact, the resulting scheduling scheme for MSs is prone to deterioration in practical implementation when the dynamic nature of LSs is neglected. Therefore, this paper presents a multi-objective model for dual-service integrated scheduling of manufacturing and logistics (DISML) and proposes an improved non-dominated sorting genetic algorithm-II (INSGA-II) to solve it. The integration of manufacturing and logistics processes introduces complex constraints, making it challenging to properly represent the solution. To address this challenge, a novel three-layer encoding approach is designed and its feasibility is demonstrated through directed graphs. Additionally, several problem-dependent heuristics are developed to enhance solving efficiency. Experimental results show that INSGA-II outperforms other algorithms in terms of IGD and C metric in 96% and 83% of instances, respectively. The results also demonstrate the advantages of the DISML mode over the decentralized scheduling mode in terms of solution quality and efficiency. Our proposed model and the results presented here provide managers with a new tool to help them schedule MSs and LSs more effectively, thereby improving production efficiency, reducing costs and unexpected delays in execution.