Title :
City group optimization
Author :
Yang, Yijun ; Duan, Haibin
Author_Institution :
Bio-inspired Autonomous Flight Systems (BAFS) Research Group, School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing 100191, P.R. China
Abstract :
In this paper, we propose a novel swarm intelligence optimization algorithm-city group optimization (CGO). CGO loosely mimics the evolution of city group. The basic components of CGO include road network, position updating rules, and transportation hub updating. These components are inspired by the evolutionary phenomena in city group. The detailed implementation procedure is also given. Series of comparative experiments on six benchmark functions with particle swarm optimization (PSO) are conducted, and the results verify the feasibility and effectiveness of our proposed CGO in solving continuous optimization problems.
Keywords :
Benchmark testing; Cities and towns; Optimization; Particle swarm optimization; Roads; Standards; City group optimization (CGO); Continuous problems; Swarm intelligence;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7260034
