Examining the role of perception, social and private information in honey bee foraging algorithms. (1st January 2013)

• Record Type: Journal Article
• Authors: Brabazon, Anthony; Cui, Wei; O'Neill, Michael
• Is Part Of: International journal of innovative computing and applications. Volume 5:Number 4(2013)
• Page Start: 240
• Page End: 261
• Publication Date: 2013-01-01
• Subjects: honey bee algorithms -- social foraging -- optimisation -- social information -- private information -- perception; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

The last decade has seen the development of a family of powerful optimisation algorithms inspired by the foraging behaviours of honey bees. A key component of these algorithms is the concept of 'recruitment' whereby successful foragers transmit information to other colony members concerning the location of discovered resources and thereby 'recruit' for that location. However, real-world foraging by honey bees is much more complex and embeds a number of additional features, including individual sensory 'perception', 'noisy' recruitment, and 'private information' (memory). In this study, we develop a series of algorithms which embed these features and assess the impact of each on the effectiveness of the resulting search performance on a series of benchmark problems representing differing resource landscapes. The simulation results support findings from the empirical study of real-world honey bees that recruitment is not a unique driver of successful foraging activity and that private information also plays an important role. This finding is relevant for the design of honey bee optimisation algorithms.