Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Review Help
Search
Nature-inspired algorithms and applied optimization
Yang X., Springer International Publishing, New York, NY, 2018. 330 pp. Type: Book (978-3-319676-68-5)
Date Reviewed: Sep 26 2018

Optimization problems occur in engineering and other fields. They are often difficult to solve efficiently, as they are mostly computationally hard (in complexity theory parlance). One way of solving these problems is by seeking inspiration from nature, so we have algorithms based on the behavior of ants, bats, bees, cuckoos, fireflies, glow-worms, and so on. This book on nature-inspired algorithms and applied optimization is volume 744 in Springer’s “Studies in Computational Intelligence” series. Editor Xin-She Yang has developed several algorithms for engineering optimization and published several books, including some on nature-inspired algorithms. His work on cuckoo search, firefly algorithms, and bat-inspired algorithms is highly cited. This book comprises 14 chapters. It is meant to be a pragmatic reference for professionals, students, and researchers.

Nature-inspired algorithms have become very popular; however, frameworks for analyzing them are just evolving. In the first chapter, Xin-She Yang looks at the characteristics of nature-inspired algorithms and attempts to analyze them quantitatively and qualitatively. He makes use of concepts such as fixed point theory, dynamical system theory, and the Markov chain Monte Carlo (MCMC) framework.

As discussed in chapter 2, “a fundamental result in optimization [is the] no free lunch theorem, [which proves] that all non-resampling optimization algorithms perform equally, averaged over all problems.” The authors show how comprehending this theorem and its extensions helps with interpreting the dynamics of an optimization algorithm and understanding how those dynamics pertain to the properties of optimization problems.

The cuckoo search algorithm is widely used for solving nonlinear global optimization problems. Chapter 3 studies the global convergence of a simplified version of this algorithm using a Markov chain framework. The fourth chapter applies a bat algorithm for solving a variant of the vehicle routing problem that has time windows. Chapter 5 reviews flower pollination algorithms and their variants, which have been developed since 2012. These algorithms have demonstrated their transcendence over other metaheuristic algorithms for solving real-world problems.

The sixth chapter surveys hyper-complex spaces that employ quaternion and octonion algebras, studying their use in surmounting the possible shortcomings of some optimization techniques. These algebras are shown to be beneficial when compared to those obtained via standard search spaces. Chapter 7 focuses on B-spline curve fitting using a variant of simulated annealing that includes “random walks based on the Lévy distribution.” Examples illustrate the method’s performance.

Flower pollination algorithms are widely used in solving engineering problems. Hence, their applications are reviewed in chapter 8. The ninth chapter looks at case studies involving bat algorithms and bidirectional bat algorithms. Research has shown that premature convergence may happen when the bat algorithm gets stuck at a local optimum. To sidestep this, directional echolocation has been innovated to develop the directional bat algorithm. Chapter 10 utilizes flower pollination algorithms for feature selection and knapsack problems and presents their worth. Firefly algorithms have been in existence for a decade; chapter 11 considers their applications and future prospects. The twelfth chapter discusses a procedure for generating many alternatives to an optimal solution, all at the same time, using a firefly algorithm. The effectiveness of this approach is exemplified. Chapter 13 looks at optimization problems related to relay placement in wireless butterfly networks. The last chapter (14) is on bat algorithms, their variants, and their practical applications to optimization problems occurring in real-life engineering.

This book presents recent developments in nature-inspired algorithms and optimization and includes many case studies. Both theory and practice are showcased. Each chapter reviews the latest research, contains scores of references to the literature, and may be read independently. The contributing authors are experts in the field from various parts of the world. This highly recommended book--a snapshot of recent research in the field of nature-inspired algorithms--would be a useful reference work for its intended audience.

Reviewer:  S. V. Nagaraj Review #: CR146252 (1812-0618)
Bookmark and Share
  Reviewer Selected
Featured Reviewer
 
 
Optimization (G.1.6 )
 
 
Nonnumerical Algorithms And Problems (F.2.2 )
 
 
Numerical Algorithms And Problems (F.2.1 )
 
Would you recommend this review?
yes
no
Other reviews under "Optimization": Date
A general-purpose global optimizer: implementation and applications
Pronzato L., Walter E., Venot A., Lebruchec J. Mathematics and Computers in Simulation XXVI(5): 412-422, 1984. Type: Article
Jul 1 1985
Minkowski matrices.
Cryer C. ACM Transactions on Mathematical Software 9(2): 199-214, 1983. Type: Article
Feb 1 1985
Numerical optimization techniques
Evtushenko Y., Springer-Verlag New York, Inc., New York, NY, 1985. Type: Book (9789780387909493)
Jun 1 1986
more...

E-Mail This Printer-Friendly
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright 1999-2024 ThinkLoud®
Terms of Use
| Privacy Policy