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Written in an accessible and easy-to-read style, this
cutting-edge book presents advanced solutions to current
and future telecommunications optimization problems. The
field of telecommunications is growing and changing ever
more rapidly, presenting new real-world problems for
optimization researchers to address. Telecommunications
engineers tend to know all about the problems involved but
are often not aware of developments in computer science
and artificial intelligence that might solve those problems.
This unique book takes a...

This book constitutes the refereed post-workshop proceedings of the AISB International Workshop on Evolutionary Computing, held in Manchester, UK, in April 1997.
The 22 strictly reviewed and revised full papers presented were selected for inclusion in the book after two rounds of refereeing. The papers are organized in sections on evolutionary approaches to issues in biology and economics, problem structure and finite landscapes, evolutionary machine learning and classifier systems, evolutionary scheduling, and more techniques and applications of evolutionary algorithms.

This volume contains a selection of papers presented at the 9th Workshop on Membrane Computing, WMC9, which took place in Edinburgh, UK, during July 28 31,2008. The ?rst three workshopson membrane computing were or- nized in Curtea de Arge, s, Romania they took place in August 2000 (with the proceedings published in Lecture Notes in Computer Science, volume 2235), in August 2001 (with a selection of papers published as a special issue of Fun- menta Informaticae, volume 49, numbers 1 3, 2002), and in August 2002 (with the proceedings published in Lecture Notes in Computer Science, volume...

Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researchers in evolutionary computation (EC) have turned their attention to these problems. They understand the power of EC to rapidly search very large and complex spaces and return reasonable solutions. While these researchers are increasingly interested in problems from the biological sciences, EC and...

Evolutionary Computation (EC) deals with problem solving, optimization, and machine learning techniques inspired by principles of natural evolution and - netics. Just from this basic de?nition, it is clear that one of the main features of theresearchcommunityinvolvedinthestudyofitstheoryandinitsapplications is multidisciplinarity. For this reason, EC has been able to draw the attention of an ever-increasing number of researchers and practitioners in several ?elds. In its 6-year-long activity, EvoNet, the European Network of Excellence in Evolutionary Computing, has been the natural reference...