Title :
A hybrid biogeography-based optimization and fireworks algorithm
Author :
Bei Zhang ; Min-Xia Zhang ; Yu-Jun Zheng
Author_Institution :
Coll. of Comput. Sci. & Technol., Zhejiang Univ. of Technol., Hangzhou, China
Abstract :
The paper presents a hybrid biogeography-based optimization (BBO) and fireworks algorithm (FWA) for global optimization. The key idea is to introduce the migration operator of BBO to FWA, in order to enhance information sharing among the population, and thus improve solution diversity and avoid premature convergence. A migration probability is designed to integrate the migration of BBO and the normal explosion operator of FWA, which can not only reduce the computational burden, but also achieve a better balance between solution diversification and intensification. The Gaussian explosion of the enhanced FWA (EFWA) is reserved to keep the high exploration ability of the algorithm. Experimental results on selected benchmark functions show that the hybrid BBO FWA has a significantly performance improvement in comparison with both BBO and EFWA.
Keywords :
optimisation; probability; BBO; EFWA; Gaussian explosion; enhanced FWA; fireworks algorithm; global optimization; hybrid biogeography-based optimization; information sharing; migration probability; normal explosion operator; premature convergence; solution diversity; Benchmark testing; Convergence; Explosions; Optimization; Sociology; Sparks; Statistics;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900289