[Comp-neuro] Call for Chapters - Nature-Inspired Optimisation, Springer SCI ***a friendly reminder***

Raymond Chiong 1c15501 at gmail.com
Mon May 26 15:30:21 CEST 2008


---------- Forwarded message ----------
From: Raymond Chiong
Date: Thu, May 15, 2008 at 11:52 PM
Subject: Call for Chapters - Nature-Inspired Optimisation, Springer SCI


 Dear Colleagues,



We have received many good proposals during the first round of our call for
chapters. In this second round, we would like to focus particularly on the
following areas:

(1) novel algorithms for optimisation

(2) optimisation in planning, scheduling and timetabling problems

(3) the use of artificial immune systems in optimisation

If you are interested in this publication, please drop me a short reply at
rchiong at swinburne.edu.my.



Best wishes,

Raymond

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~





CALL FOR CHAPTERS

==================

Proposals Submission Deadline: 31 MAY 2008 (flexible)

Full Chapters Due: 15 JULY 2008 (strict deadline)



Nature-Inspired Algorithms for Optimisation

A volume edited by Raymond Chiong



To be published by Springer-Verlag in the series Studies in Computational
Intelligence (SCI)



Book Objectives & Mission:

Nature has always been a source of inspiration. In recent years, new
concepts, techniques and computational applications stimulated by nature are
being continually proposed and exploited to solve a wide range of
optimisation problems in diverse fields. Various kinds of nature-inspired
algorithms have been designed and applied, and many of them are producing
high quality solutions to a variety of real-world applications and
optimisation problems, including scheduling, manufacturing, logistics, space
allocation, stock cutting, anomaly detection, engineering design, software
testing, bioinformatics and data mining, etc. The success of these
algorithms has led to competitive advantages and cost savings not only to
the industry but also the society at large.



The use of nature-inspired algorithms stands out to be promising due to the
fact that many real-world problems have become increasingly complex. The
size and complexity of the optimisation problems nowadays require the
development of methods and solutions whose efficiency is measured by their
ability to find acceptable results within a reasonable amount of time.
Despite there is no guarantee of finding the optimal solution, approaches
based on the influence of biology and life sciences such as evolutionary
algorithms, neural networks, ant systems, swarm intelligence, artificial
immune systems, and many others have been shown to be highly practical and
provided state-of-the-art solutions to various optimisation problems.



The aim of this book is to provide a central source of reference by
collecting and disseminating the progressive body of knowledge on
nature-inspired algorithms and their applications. The main focus will be
the implementation of novel nature-inspired solutions for optimisation based
on empirical studies.



Recommended topics include, but are not limited to, the following:



Methods:

-evolutionary algorithms

-memetic algorithms

-neural networks

-artificial life

-particle swarm optimisation

-ant colony optimisation

-artificial immune systems

-membrane, molecular, cellular and DNA computing

-tabu search, simulated annealing, etc

-hybrid methods with metaheuristics, machine learning, game theory,
mathematical programming, constraint programming, co-evolutionary learning,
etc



Applications:

-evolutionary games

-evolutionary economics

-production, logistics and transportation

-telecommunications and engineering design

-planning, scheduling and timetabling

-bioinformatics and data mining

-grid computing and computer security

-software testing and software self assembly

-numerical and combinatorial optimisation

-multi-objective optimisation, dynamic optimisation, problems with
uncertainty, etc

-integration of natural computing techniques in intelligent systems

-optimisation strategies in robotics path planning, task allocation and
coordination

-optimisation and control of highly nonlinear, large scale or networked
engineering

-successful optimisations in the fields of business, science and engineering



Submission Procedure:

Researchers and practitioners are invited to submit on or before May 31,
2008 a 1-2 page proposal to rchiong at swinburne.edu.my clearly explaining the
mission and concerns of his or her proposed chapter. Authors of accepted
proposals will be notified in 2-3 weeks time about the status of their
proposals. Full chapters are expected to be submitted by July 15, 2008. All
submitted chapters will be reviewed by at least three reviewers.



About the series Studies in Computational Intelligence:

The series Studies in Computational Intelligence (SCI) publishes new
developments and advances in the various areas of computational intelligence
- quickly and with a high quality. The intent is to cover the theory,
applications, and design methods of computational intelligence, as embedded
in the fields of engineering, computer science, physics and life science, as
well as the methodologies behind them. The series contains monographs,
lecture notes and edited volumes in computational intelligence spanning the
areas of neural networks, connectionist systems, genetic algorithms,
evolutionary computation, artificial intelligence, cellular automata,
self-organising systems, soft computing, fuzzy systems, and hybrid
intelligent systems. Critical to both contributors and readers are the short
publication time and world-wide distribution - this permits a rapid and
broad dissemination of research results.



Inquiries and submissions can be forwarded electronically or by mail to:

Raymond Chiong

Head of Intelligent Informatics Research Group

School of Computing & Design

Swinburne University of Technology (Sarawak Campus)

State Complex, 93576 Kuching

Sarawak, Malaysia

Tel.: +60 82 416 353 • Fax: +60 82 423 594

E-mail: rchiong at swinburne.edu.my
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