Abstract Machine Learning (ML) is a branch of artificial intelligence that studies algorithms
able to learn autonomously, directly from the input data. Over the last decade, ML …

Manufacturing organizations need to use different kinds of techniques and tools in order to
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining …

Today's manufacturing systems are becoming increasingly complex, dynamic, and
connected. The factory operations face challenges of highly nonlinear and stochastic activity …

Because of their cross-functional nature in the company, enhancing Production Planning
and Control (PPC) functions can lead to a global improvement of manufacturing systems …

There has been an increased interest in resilient supplier selection in recent years, much of
it focusing on forecasting the disruption probabilities. We conceptualize an entirely different …

Due to the influence of dynamic changes in the manufacturing environment, a single
dispatching rule (SDR) cannot consistently attain better results than other rules for dynamic …

The Covid-19 outbreak, which emerged in 2020, became the top priority of the world. The
fight against this disease, which has caused millions of people's deaths, is still ongoing, and …

While attracting increasing research attention in science and technology, Machine Learning
(ML) is playing a critical role in the digitalization of manufacturing operations towards …

Resource allocation systems (RASs) belong to a kind of discrete event system commonly
seen in the industry. In such systems, available resources are allocated to concurrently …

Dynamic scheduling is crucial for semiconductor manufacturing as product-mix is increasing
with shortening product life cycle. However, the present problem is challenging owing to …