Flexible job shop scheduling (FJSP) has garnered enormous attention within the realm of
smart manufacturing, where, beyond job sequencing, the selection of machines holds …

In this paper, Deep Q-Network (DQN) was adopted to solve the Job shop Scheduling
Problem (JSP) in the smart factory process. On the other hand, cloud computing has …

Manufacturing is involved with complex job shop scheduling problems (JSP). In smart
factories, edge computing supports computing resources at the edge of production in a …

With the rapid development of economic globalization and green manufacturing, traditional
flexible job shop scheduling has evolved into the low-carbon heterogeneous distributed …

Dynamic flexible job shop scheduling (DFJSS) aims to achieve the optimal efficiency for
production planning in the face of dynamic events. In practice, deep Q-network (DQN) …

For smart factories in the Industry 4.0 era, edge devices can be used to run intelligent
software packages (ie, manufacturing services) to support manufacturing activities of …

The flexible job shop scheduling problem (FJSP) is an important production scheduling
problem in intelligent manufacturing. How to model the complex FJSP more accurately and …

The production process of a smart factory is complex and dynamic. As the core of
manufacturing management, the research into the flexible job shop scheduling problem …

In the context of Industry 4.0 and intelligent manufacturing, AGVs are widely used in flexible
job shop resource transportation, which sharply increases the uncertainty and complexity of …

Abstract The Flexible Job Shop Scheduling Problem (FJSP), a classic NP-hard optimization
challenge, has a direct impact on manufacturing system efficiency. Considering that the …