Foraging-Inspired Optimisation Algorithms

• Main Authors: Brabazon, Anthony (Author, http://id.loc.gov/vocabulary/relators/aut), McGarraghy, Seán (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: Natural Computing Series,
• Subjects: Computers.; Computational intelligence.; Artificial intelligence.; Operations research.; Management science.; Decision making.; Theory of Computation.; Computational Intelligence.; Artificial Intelligence.; Operations Research, Management Science.; Operations Research/Decision Theory.

This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they...

Table of Contents:

• Introduction
• Formal Models of Foraging
• Sensor Modalities
• Individual and Social Learning
• Introduction to Foraging Algorithms
• Mammals
• Bird Foraging Algorithms
• Fish Algorithms
• Ant Foraging Algorithms
• Honeybee Inspired Algorithms
• Bioluminescence Algorithms
• Spider Algorithms
• Worm Algorithm
• Bacteria Inspired Algorithms
• Slime Mould Foraging
• Plant Foraging Algorithms
• Group Search and Predatory Search
• Evolving Foraging Algorithms
• Conclusions.