Title: Hybrid BBO and GA algorithms based on elites operation

Authors: Wuzhao Li; Weian Guo; Lei Wang; Qi Kang; Qidi Wu

Addresses: Department of Electrical Engineering and Electronics, Tongji University, Shanghai, 601804, China; Jiaxing Vocational Technical College, Zhejiang, Jiaxing, 314036, China ' Department of Electrical Engineering and Electronics, Tongji University, Shanghai, 601804, China ' Department of Electrical Engineering and Electronics, Tongji University, Shanghai, 601804, China ' Department of Electrical Engineering and Electronics, Tongji University, Shanghai, 601804, China ' Department of Electrical Engineering and Electronics, Tongji University, Shanghai, 601804, China

Abstract: As a novel heuristic optimisation algorithm, biogeography-based optimisation (BBO) has a huge potential to be further developed. Genetic algorithm (GA) is a famous algorithm in optimisation as well. In this paper, two hybrid algorithms of BBO and GA are proposed based on elites operations. According to the property of the two algorithms, we optimised the elites' migration model in BBO by using GA. The one is named global migration hybrid strategy (GMHS), and the other is hierarchical migration hybrid strategy (HMHS). From the test results, it is obvious that the two strategies both perform better than BBO or GA alone. In addition, some comparisons among the new two hybrid strategies and other famous hybrid algorithms are shown in this paper. And an application of semiconductor manufacturing lines is implemented by the hybrid algorithm. According to the results, we know the hybrid strategies have a better capability to solve optimisation problems.

Keywords: biogeography-based optimisation; BBO; genetic algorithms; GAs; hybrid strategy; migration; elites operation; semiconductor manufacturing.

DOI: 10.1504/IJMIC.2013.051928

International Journal of Modelling, Identification and Control, 2013 Vol.18 No.1, pp.9 - 17

Available online: 05 Feb 2013 *

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