This article proposes a new paradigm of asymmetric multifractality in financial time series,
where the scaling feature varies over two adjacent intervals. The proposed approach first …

This paper presents a rigorous investigation into the multiresolution cross-correlation and
causality between European energy markets and geopolitical risk (GPR). Using daily …

ABSTRACT The Capacitated Vehicle Routing Problem (CVRP) is a well-known
combinatorial optimisation problem used to design an optimal route for a fleet of capacitated …

Forecasting has always been the cornerstone of machine learning and statistics. Despite the
great evolution of the time series theory, forecasters are still in the hunt for better models to …

Forecasting is a very important and difficult task for various economic activities. Despite the
great evolution of time series modeling, forecasters are still in the hunt for better strategies to …

The aim of this paper is to further study the rich vehicle routing problem (RVRP), which is a
well-known combinatorial optimization problem arising in many transportation and logistics …

In power industry and management, given the peculiarity and high complexity of the time
series, it is highly requested to make models more flexible and well adapted to the data, in …

Due to the rapid growth of the number of passengers over the few recent decades, air traffic
forecasting has become a crucial tool for digital transportation systems, playing a …

Many methods of image acquisition from medical multidimensional data rely on continuous
techniques whereas in fact they are used in a finite discrete field. The discretization step is …

Several extrapolation strategies have been proposed in the literature to accelerate the EM
algorithm, with varying degrees of success. One advantage of extrapolation methods is their …