The concept of a Digital Twin (DT) has stood out among the emerging digitization
technologies and been embraced by US and EU governments and companies. Practitioners …

Scenarios have become a powerful tool in integrated assessment and policy analysis for
climate change. Socio-economic and climate scenarios are often combined to assess …

In this paper, we propose a general data-driven framework that unifies the valuation and risk
measurement of financial derivatives, which is especially useful in markets with thinly-traded …

We review simulation optimization methods and discuss how these methods underpin
modern artificial intelligence (AI) techniques. In particular, we focus on three areas …

In a world heading towards applications, in science and industry, based on big data
processing, the ability to elaborate streams of data is becoming more important every day …

This paper addresses the challenges of low‐carbon sourcing in intertwined supply chains by
proposing a data‐driven control framework and a prey–predator model for sourcing …

Large-scale simulation optimization (SO) problems encompass both large-scale ranking-
and-selection problems and high-dimensional discrete or continuous SO problems …

Estimating the unknown density from which a given independent sample originates is more
difficult than estimating the mean in the sense that, for the best popular nonparametric …

We present a gradient-based algorithm for solving a class of simulation optimization
problems in which the objective function is the quantile of a simulation output random …

Multi-channel data management is crucial in a world where big data processing is
extensively used in research and business. Histogramming is a common technique …