CALL FOR CHAPTERS

Proposals Submission Deadline: 30 APRIL 2008
Full Chapters Due: 15 JULY 2008

 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 nature-inspired solutions for optimisation based on empirical studies.

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

• Methods:
  o  evolutionary algorithms
  o  memetic algorithms
  o  neural networks
  o  artificial life
  o  particle swarm optimisation
  o  ant colony optimisation
  o  artificial immune systems
  o  membrane, molecular, cellular and DNA computing
  o  tabu search, simulated annealing, etc
  o  hybrid methods with metaheuristics, machine learning, game theory, mathematical programming, constraint programming, co-evolutionary learning, etc
   

• Applications:
  o  evolutionary games
  o  evolutionary economics
  o  production, logistics and transportation
  o  telecommunications and engineering design
  o  planning, scheduling and timetabling
  o  bioinformatics and data mining
  o  cooperative decision support systems
  o  grid computing and computer security
  o  software testing and software self assembly
  o  numerical and combinatorial optimisation
  o  multi-objective optimisation, dynamic optimisation, problems with uncertainty, etc
  o  integration of natural computing techniques in intelligent systems
  o  implementation issues of natural computing techniques
  o  optimisation strategies in robotics path planning, task allocation and coordination
  o  optimisation and control of highly nonlinear, large scale or networked engineering
  o  empirical comparison of optimisation problems
  o  successful optimisations in the fields of business, science and engineering

Submission Procedure:
Researchers and practitioners are invited to submit on or before April 30, 2008 an extended abstract to rchiong@swinburne.edu.my clearly explaining the mission and concerns of his or her proposed chapter. Authors of accepted proposals will be notified in 2 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.

Important Dates:

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
School of Information Technology
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@swinburne.edu.my