Title: Improved shuffled frog leaping algorithm for continuous optimisation adapted SEVO toolbox
Authors: Hema Banati; Shikha Mehta
Addresses: Department of Computer Science, Dyal Singh College, University of Delhi, Delhi, India ' Department of Computer Science, Faculty of Mathematical Sciences, University of Delhi, 1st Floor, New Academic Block, Delhi – 110007, India
Abstract: This paper presents improved shuffled frog leaping algorithm (ISFLA) with controlled random search behaviour. The work proposes adaptation of random solution generation rule with control parameter to manage the direction of search in conventional SFLA. To evaluate the effectiveness of ISFLA, it has been compared with respect to GA, MA, PSO and SFLA for large dimensions-100, 500 and 1,000 over benchmark test problems using SEVO toolbox. Results depict that ISFLA performs considerably better for all benchmark problems. Results also demonstrated the utility and simplicity of SEVO toolbox for simulating new algorithms. ANOVA test substantiated the statistical significance of the obtained results.
Keywords: shuffled frog leaping algorithm; SFLA; evolutionary optimisation; swarm optimisation; benchmark test problems; SEVO tool; controlled random search; swarm intelligence; simulation.
International Journal of Advanced Intelligence Paradigms, 2013 Vol.5 No.1/2, pp.31 - 44
Received: 04 Jul 2012
Accepted: 19 Nov 2012
Published online: 30 Jul 2014 *