Evolutionary algorithms (EA), a class of stochastic search methods based on the principles
of natural evolution, have received widespread acclaim for their exceptional performance in …

Dynamic events and transportation constraints would significantly affect the full utilization of
resources and the reduction of production costs in distributed job shops. Therefore, in this …

Multi-task optimization problems in the real world often contain constraints. When dealing
with these problems, it is necessary to consider multiple tasks and their respective …

Hyper-heuristics are general purpose search methods for solving computationally difficult
problems. A selection hyper-heuristic is composed of two key components: a heuristic …

Silicon electrodes are widely used in semiconductor etching machines. The periodic
consumption of silicon electrodes has become an important consumable in wafer …

In the process of the integrated scheduling of multi-variety and small-batch complex
products, the process structure and attribute characteristics are often ignored, which affects …

The reinforcement learning based hyper-heuristics (RL-HH) is a popular trend in the field of
optimization. RL-HH combines the global search ability of hyper-heuristics (HH) with the …

Conducting a maturity assessment allows companies to measure their readiness in
implementing novel technologies. However, this task is challenging due to the …

In the post-pandemic era, more manufacturers have expedited the shift from centralized to
distributed manufacturing to enhance supply chain resilience. Along with this, the distributed …

As the product mix in production changes dramatically, cell reconfiguration is requisite to
smoothen the production process. Meanwhile, multiple production modes are …