Firefly algorithm, stochastic test functions and design optimisation

Yang, Xin-She (2010) Firefly algorithm, stochastic test functions and design optimisation. International Journal of Bio-Inspired Computation , 2 (2). pp. 78-84. ISSN 1758-0366

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Official URL: http://dx.doi.org/10.1504/IJBIC.2010.032124

Abstract

Modern optimisation algorithms are often metaheuristic, and they are very promising in solving NP-hard optimisation problems. In this paper, we show how to use the recently developed firefly algorithm to solve non-linear design problems. For the standard pressure vessel design optimisation, the optimal solution found by FA is far better than the best solution obtained previously in the literature. In addition, we also propose a few new test functions with either singularity or stochastic components but with known global optimality and thus they can be used to validate new optimisation algorithms. Possible topics for further research are also discussed. (from publisher's website)

Item Type:Article
Keywords (uncontrolled):firefly algorithm; design optimisation; metaheuristics; stochastic test function; particle swarm optimisation; PSO; bio-inspired computation; nonlinear design; pressure vessel design.
Research Areas:Middlesex University Schools and Centres > School of Science and Technology > Computer and Communications Engineering
ID Code:9559
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Deposited On:19 Nov 2012 11:19
Last Modified:04 Aug 2014 14:22

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