Data science and big data analytics (DS &BDA) methodologies and tools are used
extensively in supply chains and logistics (SC &L). However, the existing insights are …

With advances in technologies, data science techniques, and computing equipment, there
has been rapidly increasing interest in the applications of reinforcement learning (RL) to …

Industry 5.0 is a combination of organisational principles and technologies to design and
manage operations and supply chains as resilient, sustainable, and human-centric systems …

A large variety of models have been developed in the last two decades aiming at supply
chain (SC) stress-testing and resilience. New digital and artificial intelligence (AI) …

Purpose This paper aims to investigate hypothesized relationships between the Internet of
things (IoT) and big data analytics (BDA) with supply chain visibility (SCV) and operational …

Our research strives to examine how simulation models of logistics systems can be
produced automatically from verbal descriptions in natural language and how human …

The ability to understand and explain the outcomes of data analysis methods, with regard to
aiding decision-making, has become a critical requirement for many applications. For …

The COVID-19 pandemic's impacts have been devastating for the global economy, and
particularly for manufacturing companies. Many firms were unprepared for a crisis of this …

Consumers' dramatic demand has a pernicious effect throughout the supply chain. It
exacerbates inventory distortion because of significant revenue loss caused by stock-level …

In the literature, machine learning (ML) and artificial intelligence (AI) applications tend to
start with examples that are irrelevant to process engineers (eg classification of images …