LFOA

If you want to understand the LFOA, You have to read the information below.

Fruit Fly Optimization Algorithm (FFOA) Introduction

The book entitled by “Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms”, by “Bo Xing and Wen-Jing Gao, 2014, Springer.

Part II Biology-based CI Algorithms: Fruit Fly Optimization Algorithm (FFOA)

Chapter 11:

In this chapter, we present a novel optimization algorithm called fruit fly optimization algorithm (FFOA) which is inspired by the behavior of fruit flies. We first describe the general knowledge about the foraging behavior of fruit flies in Sect. 11.1. Then, the fundamentals and performance of FFOA are introduced in Sect. 11.2. Finally, Sect. 11.3 summarizes this chapter.

Foreword to this book

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms”

Computational intelligence (CI) is a relatively new discipline, and accordingly, there is little agreement about its precise definition. Nevertheless, most academicians and practitioners would include techniques such as artificial neural network, fuzzy systems, many versions of evolutionary algorithms (e.g. evolution strategies, genetic algorithm, genetic programming, differential evolution), as well as ant colony optimization, artificial immune systems, multi-agent systems, particle swarm optimization, and the hybridization versions of these, under the umbrella of CI.

In contrast to this common trend, Bo and Wen-Jing offer us a brand new perspective in the field of CI research through their book entitled Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms.

 This book is unique because it contains in one source an overview of a wide range of newly developed CI algorithms that are normally found in scattered resources.

The authors succeed in identifying this vast amount of novel CI algorithms and grouping them into four large classes, namely, biology-, physics-, chemistry-, and mathematics-based CI algorithms.

 Furthermore, the organization of the book is such that each algorithm covered in the book contains the corresponding core working principles and some preliminary performance evaluations. This style would, no doubt, lead to the further development of these fascinating algorithms. This book will be beneficial to a broad audience: First, university students, particularly those pursuing their postgraduate studies in advanced subjects; Second, the algorithms introduced in this book can serve as foundations for researchers to build bodies of knowledge in the fast growing area of CI research; Finally, practitioners can also use the algorithms presented in this book to solve and analyze specific real-world problems. Overall, this book makes a worthwhile read and is a welcome edition to the CI literature.

By Zbigniew Michalewicz

Adelaide, Australia, September 2013