Wireless sensor networks (WSNs) have attracted substantial research interest, especially in
the context of performing monitoring and surveillance tasks. However, it is challenging to …

In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …

This article presents a review and a comparative analysis between frameworks for solving
optimization problems using metaheuristics. The aim is to identify both the desirable …

In this paper, we investigate the problem of scheduling precedence-constrained parallel
applications on heterogeneous computing systems (HCSs) like cloud computing …

This article presents a multi-agent framework for optimization using metaheuristics, called
AMAM. In this proposal, each agent acts independently in the search space of a …

Multiobjective evolutionary algorithms (MOEAs) are typically proposed, studied, and applied
as monolithic blocks with a few numerical parameters that need to be set. Few works have …

In this paper, we present and define the bi-objective Green Vehicle Routing Problem GVRP
in the context of green logistics. The bi-objective GVRP states for the problem of finding …

The timetabling step in railway planning is based on the estimation of the running times.
Usually, they are estimated as the shortest running time increased of a short time …

This paper discusses simple local search approaches for approximating the efficient set of
multiobjective combinatorial optimization problems. We focus on algorithms defined by a …

The success of metaheuristic optimization methods has led to the development of a large
variety of algorithm paradigms. However, no algorithm clearly dominates all its competitors …