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Goldsmiths - University of London

Stochastic Diffusion Optimisation: the application of partial function evaluation and stochastic recruitment in Swarm Intelligence optimisation

Bishop, Mark (J. M.); De Meyer, K. and Nasuto, S.J. 2006. Stochastic Diffusion Optimisation: the application of partial function evaluation and stochastic recruitment in Swarm Intelligence optimisation. In: Ajith Abraham; Crina Grosam and Vitorino Ramos, eds. Studies in Computational Intelligence (31): Stigmergic Optimization. Verlag: 978-0312097264, pp. 185-207. ISBN 978-0312097264 [Book Section]

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Abstract or Description

The concept of partial evaluation of ¯tness functions, together with mechanisms manipulating the resource allocation of population based search methods, are presented in the context of Stochastic Diffusion Search, a novel swarm intelligence metaheuristic that has many similarities with ant and evolutionary algorithms. It is demonstrated that the stochastic process ensuing from
these algorithmic concepts has properties that allow the algorithm to optimise noisy fitness functions, to track moving optima, and to redistribute the population after quantitative changes in the fitness function. Empirical results are used to validate theoretical arguments.

Item Type: Book Section

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
2006Published

Item ID:

15136

Date Deposited:

01 Dec 2015 12:02

Last Modified:

20 Jun 2017 09:39

URI: http://research.gold.ac.uk/id/eprint/15136
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