7,176 research outputs found
Guest editorial: Memetic computing in the presence of uncertainties
Copyright @ Springer-Verlag 2010.The Guest Editors acknowledge the research support by the Academy of Finland, Akatemiatutkija 130600, Algorithmic
Design Issues in Memetic Computing, and by the UK Engineering and Physical Sciences Research Council (EPSRC) Project: Evolutionary Algorithms for Dynamic Optimisation Problems, under Grant EP/E060722/1
A Memetic Algorithm for the Generalized Traveling Salesman Problem
The generalized traveling salesman problem (GTSP) is an extension of the
well-known traveling salesman problem. In GTSP, we are given a partition of
cities into groups and we are required to find a minimum length tour that
includes exactly one city from each group. The recent studies on this subject
consider different variations of a memetic algorithm approach to the GTSP. The
aim of this paper is to present a new memetic algorithm for GTSP with a
powerful local search procedure. The experiments show that the proposed
algorithm clearly outperforms all of the known heuristics with respect to both
solution quality and running time. While the other memetic algorithms were
designed only for the symmetric GTSP, our algorithm can solve both symmetric
and asymmetric instances.Comment: 15 pages, to appear in Natural Computing, Springer, available online:
http://www.springerlink.com/content/5v4568l492272865/?p=e1779dd02e4d4cbfa49d0d27b19b929f&pi=1
Memetic Multilevel Hypergraph Partitioning
Hypergraph partitioning has a wide range of important applications such as
VLSI design or scientific computing. With focus on solution quality, we develop
the first multilevel memetic algorithm to tackle the problem. Key components of
our contribution are new effective multilevel recombination and mutation
operations that provide a large amount of diversity. We perform a wide range of
experiments on a benchmark set containing instances from application areas such
VLSI, SAT solving, social networks, and scientific computing. Compared to the
state-of-the-art hypergraph partitioning tools hMetis, PaToH, and KaHyPar, our
new algorithm computes the best result on almost all instances
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Memetic: from meeting memory to virtual ethnography & distributed video analysis
The JISC-funded Memetic2 project was designed as knowledge management and project memory support for teams meeting via the Access Grid environment (Buckingham Shum et al, 2006). This paper describes how these capabilities also enable it to serve as a novel distributed video analysis tool to support interaction analysis. Memetic technologies can be used to record, annotate and discuss sessions recorded within a flexible, visual hypermedia environment called Compendium. We propose that beyond the use originally conceived, the Memetic toolset could find wide ranging applications within social science for virtual ethnography and data analysis
Composing Distributed Data-intensive Web Services Using a Flexible Memetic Algorithm
Web Service Composition (WSC) is a particularly promising application of Web
services, where multiple individual services with specific functionalities are
composed to accomplish a more complex task, which must fulfil functional
requirements and optimise Quality of Service (QoS) attributes, simultaneously.
Additionally, large quantities of data, produced by technological advances,
need to be exchanged between services. Data-intensive Web services, which
manipulate and deal with those data, are of great interest to implement
data-intensive processes, such as distributed Data-intensive Web Service
Composition (DWSC). Researchers have proposed Evolutionary Computing (EC)
fully-automated WSC techniques that meet all the above factors. Some of these
works employed Memetic Algorithms (MAs) to enhance the performance of EC
through increasing its exploitation ability of in searching neighbourhood area
of a solution. However, those works are not efficient or effective. This paper
proposes an MA-based approach to solving the problem of distributed DWSC in an
effective and efficient manner. In particular, we develop an MA that hybridises
EC with a flexible local search technique incorporating distance of services.
An evaluation using benchmark datasets is carried out, comparing existing
state-of-the-art methods. Results show that our proposed method has the highest
quality and an acceptable execution time overall.Comment: arXiv admin note: text overlap with arXiv:1901.0556
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