With the rapid development of cloud computing, scheduling the complex scientific workflow
on the cloud becomes an extraordinarily challenging problem. Especially, the workflow …

Abstract Graph Layout Problems refer to a family of optimization problems where the aim is
to assign the vertices of an input graph to the vertices of a structured host graph, optimizing a …

Graph layout problems are a family of combinatorial optimization problems that consist of
finding an embedding of the vertices of an input graph into a host graph such that an …

Inferring Boolean networks is crucial for modeling and analyzing gene regulatory networks
from a systematic perspective. However, the state-of-the-art algorithms cannot accurately …

Hyper-heuristics are widely used for solving numerous complex computational search
problems because of their intrinsic capability to generalize across problem domains. The fair …

Boolean network inference is essential for gaining insights into gene regulatory networks
through multivariate gene expression time series. However, most existing algorithms cannot …

The iterated greedy metaheuristic generates a sequence of solutions by iterating over a
constructive heuristic using destruction and construction phases. In the last few years, it has …

Reconstructing complex network structures from measurable data has become a central
issue in contemporary network science and engineering. In this paper, we tackle the …

Many cloud providers benefit from fine-grained resource management in Container as a
Service (CaaS), eg, energy savings. However, while optimizing power consumption, cloud …

Given an optimization problem, combining knowledge from both (i) structural or algorithmic
known results and (ii) new solving techniques, helps gain insight and knowledge on the …