Title :
A modified differential evolution algorithm
Author_Institution :
Sch. of Autom. & Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China
Abstract :
Differential Evolution (DE) is a simple and efficient heuristic algorithm for global optimization over continuous spaces. Because of its outstanding performance, simplicity and remarkable efficiency, DE has being used widely to deal with real-life problems. However DE has some problems such as low precision and prematurity if the scaling factor F is not chosen carefully. In this paper a modified DE algorithm(sFDE) is proposed which uses an adaptive scaling factor sF to replace the invariable factor F in basic DE. This new algorithm performs better than the basic DE over a set of benchmark functions and a practical use for data reconciliation shows its effectiveness also.
Keywords :
evolutionary computation; adaptive scaling factor; data reconciliation; global optimization; heuristic algorithm; modified differential evolution algorithm; Algorithm design and analysis; Benchmark testing; Computers; Measurement uncertainty; Optimization; Signal processing algorithms; Simulation; Adaptive; DE; Scaling Factor;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6