Nilanjan Dey - Applications of Cuckoo Search Algorithm and its Variants

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Evolutionary-based meta-heuristic approaches are effectively applied to solve complicated optimization problems in several real-world applications. One of the successful optimization algorithms is the Cuckoo Search (CS) which becomes an active research area to solve N-dimensional and linear/nonlinear optimization problems using simple mathematical processes. Based on its underpinning in 2009, CS has attracted the attention of various researchers, causing numerous variants of the basic CS with enriched performance. This book highlights the basic concepts of CS algorithm and its foremost variants and their use in solving diverse optimization problems in medical and engineering applications.

This volume entails thirteen chapters providing different CS applications for solving optimization problems. In Chap. , Dao et al. implemented a statistical-based CS algorithm for its engineering applications, such as camera-positioning device task. In such an application, CS was used to optimize the design variables, objective functions, and constraints.

In Chap. , Maroosi proposed a cuckoo search algorithm inspired from membrane systems, which can concurrently evaluate more than one cost function on parallel devices.

The editor is keen on expressing his gratitude to the contributors for the valuable contributions and the respected referees. An extended gratitude is directed to the members of the Springer team for their support. Am, the editor, wishes this book entails advanced, valuable research on Cuckoo search and its variants to solve diverse optimization engineering problems in real-world clinical applications.