Deep reinforcement learning (DRL), as a promising technique, is a new approach to solve
the job shop scheduling problem (JSSP). Although DRL method is effective for solving …

With popularity of mass customization, enterprises urgently need to improve reconfigurability
to handle rapidly changing market demands. Reconfigurable machines have been widely …

The non-waiting constraint is a crucial factor in industries with continuous production flows.
Recognizing the significance of this constraint in the manufacturing process, we propose …

The process of eliminating irrelevant, redundant and noisy features while trying to maintain
less information loss is known as a feature selection problem. Given the vast amount of the …

A U-shaped automated container terminal (ACT) has been proposed for the first time
globally and has been adopted to construct the Beibu Gulf Port ACT. In this ACT layout, the …

The no-wait job shop problem has important applications in various industries such as steel-
making and chemical processes, and its mainstream approaches are metaheuristics with …

Job-splitting is a universally recognized approach to improve production efficiency,
particularly in cases where the job lot size is excessively large. Flexible sub-lots that have …

The no-wait job-shop scheduling problem (NWJSP) exists in several real-life manufacturing
industries. It requires no waiting time between adjacent operations of the same job because …

To address the multi-flexible integrated scheduling problem with setup times, a multi-flexible
integrated scheduling algorithm is put forward. First, the operation optimization allocation …

Flexible job-shop scheduling problem (F-JSP) is an expansion of the job shop scheduling
problem (JSP) which allows an operation to be fulfilled by any machine among a set of …