Journal
ELECTRONICS LETTERS
Volume 56, Issue 24, Pages 1320-1322Publisher
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/el.2020.2144
Keywords
ant colony optimisation; neural nets; computational complexity; reliability; parallel processing; ant colony optimisation; parallelism; spiking neural P systems; SN P systems; polynomial time optimal solution; reliability; spiking neural P ant optimisation; foraging ant behaviour
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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.
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