Nature-inspired metaheuristic algorithms have attracted much attention in the last decade,
and new algorithms have emerged almost every year with a vast, ever-expanding literature …

The goal of Machine Learning to automatically learn from data, extract knowledge and to
make decisions without any human intervention. Such automatic (aML) approaches show …

Autonomous intersection management (AIM) is an innovative concept for directing vehicles
through the intersections. AIM assumes that the vehicles negotiate the right-of-way. This …

The multi-satellite control resource scheduling problem (MSCRSP) is a kind of large-scale
combinatorial optimization problem. As the solution space of the problem is sparse, the …

With the increasing number of satellite, the satellite control resource scheduling problem
(SCRSP) has been main challenge for satellite networks. SCRSP is a constrained and large …

The agile earth observation satellite (AEOS) task scheduling problem has been proven to be
NP-hard. The traditional meta-heuristics is easy to converge too early or too late, and difficult …

With the increasing number of space satellites, the demand for satellite communication
(including maneuvering, command uploading and data downloading) has also grown …

Abstract Resources scheduling in Low Earth Orbit (LEO) satellites is an important
optimization problem because of the satellitesʼ specific constraints. This article addresses a …

Imaging satellite scheduling is an NP‐hard problem with many complex constraints. This
paper researches the scheduling problem for dynamic tasks oriented to some emergency …

The problem of link prediction has attracted considerable recent attention from various
domains such as sociology, anthropology, information science, and computer sciences. In …