Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications

Andrew Lewis, Sanaz Mostaghim, Marcus Randall

Research output: Book/ReportScholarly editionResearchpeer-review

Abstract

Humanity has often turned to Nature for inspiration to help it solve its problems. The systems She provides are often based on simple rules and premises, yet are able to adapt to new and complex environments quickly and efficiently. Problems from a range of human endeavours, including, science, engineering and economics, require us to find good quality solutions in exponentially large search spaces, a task that often requires vast amounts computational resources and effort. In this book, the contributing authors solve these problems by modelling aspects of the natural world, from the flocking of birds and fish, the operation of colonies of ants through to chromosome reproduction and beyond. Many of the contributions represent extended studies of work presented at a number of workshops on Biologically-Inspired Optimisation Methods at international conferences on e-Science, Grid Computing, and Evolutionary Computation. A variety of chapters from some of the leading experts in the field present an overview of the state-of-the-art, recent advances in theoretical and practical ideas and techniques, and details of application of these methods to a range of benchmark and real world problems.
Original languageEnglish
PublisherSpringer
Number of pages360
Volume210
ISBN (Electronic)978-3-642-01262-4
ISBN (Print)978-3-642-01261-7, 978-3-642-10177-9
DOIs
Publication statusPublished - 2009

Publication series

NameStudies in Computational Intelligence
PublisherSpringer
Volume210
ISSN (Electronic)1860-949X

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Grid computing
Birds
Chromosomes
Parallel algorithms
Evolutionary algorithms
Fish
Economics

Cite this

Lewis, Andrew ; Mostaghim, Sanaz ; Randall, Marcus. / Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications. Springer, 2009. 360 p. (Studies in Computational Intelligence).
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Lewis, A, Mostaghim, S & Randall, M 2009, Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications. Studies in Computational Intelligence, vol. 210, vol. 210, Springer. https://doi.org/10.1007/978-3-642-01262-4

Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications. / Lewis, Andrew; Mostaghim, Sanaz; Randall, Marcus.

Springer, 2009. 360 p. (Studies in Computational Intelligence; Vol. 210).

Research output: Book/ReportScholarly editionResearchpeer-review

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AB - Humanity has often turned to Nature for inspiration to help it solve its problems. The systems She provides are often based on simple rules and premises, yet are able to adapt to new and complex environments quickly and efficiently. Problems from a range of human endeavours, including, science, engineering and economics, require us to find good quality solutions in exponentially large search spaces, a task that often requires vast amounts computational resources and effort. In this book, the contributing authors solve these problems by modelling aspects of the natural world, from the flocking of birds and fish, the operation of colonies of ants through to chromosome reproduction and beyond. Many of the contributions represent extended studies of work presented at a number of workshops on Biologically-Inspired Optimisation Methods at international conferences on e-Science, Grid Computing, and Evolutionary Computation. A variety of chapters from some of the leading experts in the field present an overview of the state-of-the-art, recent advances in theoretical and practical ideas and techniques, and details of application of these methods to a range of benchmark and real world problems.

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