1,415 research outputs found
A Brief Review of Cuckoo Search Algorithm (CSA) Research Progression from 2010 to 2013
Cuckoo Search Algorithm is a new swarm intelligence algorithm which based on
breeding behavior of the Cuckoo bird. This paper gives a brief insight of the advancement of the
Cuckoo Search Algorithm from 2010 to 2013.
The first half of this paper presents the publication trend of Cuckoo Search Algorithm. The
remaining of this paper briefly explains the contribution of the individual publication related to
Cuckoo Search Algorithm. It is believed that this paper will greatly benefit the reader who needs a
bird-eyes view of the Cuckoo Search Algorithm’s publications trend
Bat Algorithm: Literature Review and Applications
Bat algorithm (BA) is a bio-inspired algorithm developed by Yang in 2010 and
BA has been found to be very efficient. As a result, the literature has
expanded significantly in the last 3 years. This paper provides a timely review
of the bat algorithm and its new variants. A wide range of diverse applications
and case studies are also reviewed and summarized briefly here. Further
research topics are also discussed.Comment: 10 page
Porcellio scaber algorithm (PSA) for solving constrained optimization problems
In this paper, we extend a bio-inspired algorithm called the porcellio scaber
algorithm (PSA) to solve constrained optimization problems, including a
constrained mixed discrete-continuous nonlinear optimization problem. Our
extensive experiment results based on benchmark optimization problems show that
the PSA has a better performance than many existing methods or algorithms. The
results indicate that the PSA is a promising algorithm for constrained
optimization.Comment: 6 pages, 1 figur
Review of Metaheuristics and Generalized Evolutionary Walk Algorithm
Metaheuristic algorithms are often nature-inspired, and they are becoming
very powerful in solving global optimization problems. More than a dozen of
major metaheuristic algorithms have been developed over the last three decades,
and there exist even more variants and hybrid of metaheuristics. This paper
intends to provide an overview of nature-inspired metaheuristic algorithms,
from a brief history to their applications. We try to analyze the main
components of these algorithms and how and why they works. Then, we intend to
provide a unified view of metaheuristics by proposing a generalized
evolutionary walk algorithm (GEWA). Finally, we discuss some of the important
open questions.Comment: 14 page
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