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Books > Business & Economics > Business & management > Management & management techniques > Operational research
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Theory and Principled Methods for the Design of Metaheuristics (Paperback, Softcover reprint of the original 1st ed. 2014)
Loot Price: R2,132
Discovery Miles 21 320
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Theory and Principled Methods for the Design of Metaheuristics (Paperback, Softcover reprint of the original 1st ed. 2014)
Series: Natural Computing Series
Expected to ship within 18 - 22 working days
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Metaheuristics, and evolutionary algorithms in particular, are
known to provide efficient, adaptable solutions for many real-world
problems, but the often informal way in which they are defined and
applied has led to misconceptions, and even successful applications
are sometimes the outcome of trial and error. Ideally, theoretical
studies should explain when and why metaheuristics work, but the
challenge is huge: mathematical analysis requires significant
effort even for simple scenarios and real-life problems are usually
quite complex. In this book the editors establish a bridge between
theory and practice, presenting principled methods that incorporate
problem knowledge in evolutionary algorithms and other
metaheuristics. The book consists of 11 chapters dealing with the
following topics: theoretical results that show what is not
possible, an assessment of unsuccessful lines of empirical
research; methods for rigorously defining the appropriate scope of
problems while acknowledging the compromise between the class of
problems to which a search algorithm is applied and its overall
expected performance; the top-down principled design of search
algorithms, in particular showing that it is possible to design
algorithms that are provably good for some rigorously defined
classes; and, finally, principled practice, that is reasoned and
systematic approaches to setting up experiments, metaheuristic
adaptation to specific problems, and setting parameters. With
contributions by some of the leading researchers in this domain,
this book will be of significant value to scientists,
practitioners, and graduate students in the areas of evolutionary
computing, metaheuristics, and computational intelligence.
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