Open AccessSpiking neural P ant optimisation: a novel approach for ant colony optimisation
Author(s) -
Ramachandranpillai R.,
Arock M.
Publication year - 2020
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2020.2144
Subject(s) - ant colony optimization algorithms , foraging , ant colony , computer science , reliability (semiconductor) , scheme (mathematics) , computational complexity theory , mathematical optimization , artificial intelligence , algorithm , mathematics , ecology , biology , mathematical analysis , power (physics) , physics , quantum mechanics
This Letter introduces an optimisation method that is based on parallelism to simulate the behaviour of foraging ants using spiking neural P (SN P) systems. The proposed method is designed by collaborating several SN P systems to obtain a polynomial time optimal solution. The complexity and reliability of the method have been verified. A theoretical analysis has been performed on the measures of complexity and proved the efficiency of the scheme.