Nowadays, music-inspired phenomenon-mimicking harmony search
algorithm is fast growing with many applications. One of key
success factors of the algorithm is the employment of a novel
stochastic derivative which can be used even for discrete
variables. Instead of traditional calculus-based gradient, the
algorithm utilizes musician's experience as a derivative in
searching for an optimal solution. This can be a new paradigm and
main reason in the successes of various applications.
The goal of this book is to introduce major advances of the
harmony search algorithm in recent years. The book contains 14
chapters with the following subjects: State-of-the-art in the
harmony search algorithm structure; robotics (robot terrain and
manipulator trajectory); visual tracking; web text data mining;
power flow planning; fuzzy control system; hybridization (with
Taguchi method or SQP method); groundwater management; irrigation;
logistics; timetabling; and bioinformatics (RNA structure
prediction).
This book collects the above-mentioned theory and applications,
which are dispersed in various technical publications, so that
readers can have a good grasp of current status of the harmony
search algorithm and foster new breakthroughs in their fields using
the algorithm.
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