A hybrid social emotional optimization algorithm with Metropolis rule

Author

Wu, Jianna ; Cui, Zhihua ; Liu, Jing

Author_Institution

Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China

fYear

2011

fDate

26-29 June 2011

Firstpage

363

Lastpage

370

Abstract

Social emotional optimization algorithm (SEOA) is a novel swarm intelligent population-based optimization algorithm by simulating the human social behaviors. However, it´s diversity is decreased increased when solving high-dimensional multi-modal optimization problems. Therefore, in this paper, a new hybrid SEOA with Metropolis rule is introduced to enhance the exploration capability. To test the performance, five famous benchmarks are selected, and compared with the standard version with different dimensions. Simulation results show this hybrid algorithm can increase the global search capability significantly.

Keywords

behavioural sciences computing; optimisation; social sciences computing; global search capability; high-dimensional multimodal optimization problem; human social behavior; hybrid social emotional optimization algorithm; metropolis rule; simulating; swarm intelligent population-based optimization algorithm; Benchmark testing; Cultural differences; Decision making; Humans; Indexes; Optimization; Solids;

fLanguage

English

Publisher

ieee

Conference_Titel

Modelling, Identification and Control (ICMIC), Proceedings of 2011 International Conference on

Conference_Location

Shanghai

Type

conf

DOI

10.1109/ICMIC.2011.5973732

Filename

5973732