Slime mould foraging: an inspiration for algorithmic design. (19th February 2020)

• Record Type: Journal Article
• Authors: Brabazon, Anthony; McGarraghy, Seán
• Is Part Of: International journal of innovative computing and applications. Volume 11:Number 1(2020)
• Page Start: 30
• Page End: 45
• Publication Date: 2020-02-19
• Subjects: slime mould algorithms -- foraging-inspired algorithms -- graph optimisation -- non-neuronal organisms; 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 metaphor of 'foraging as search' provides a rich source of inspiration for the design of optimisation algorithms. An extensive literature has resulted in computer science over the past twenty years based on this, with algorithmic families such as ant colony optimisation and honeybee optimisation amongst others, being successfully applied to a wide range of real-world problems. Of course, all organisms must forage to acquire necessary resources and in recent years, increasing attention has been paid to the mechanisms by which non-neuronal organisms, in other words organisms without a central nervous system, forage. The vast majority of living organisms, encompassing some 99.5% of all biomass on earth, are non-neuronal. In this paper we introduce the plasmodial slime mould Physarum polycephalum . This non-neuronal organism is formed when individual amoebae swarm together and fuse, resulting in a large bag of cytoplasm encased within a thin membrane which acts a single organism. Inspiration has been drawn from some of its foraging behaviours to develop algorithms for graph optimisation and exemplars of these algorithms along with some suggestions for future research are presented in this paper.