Title :
Adaptive Inflationary Differential Evolution
Author :
Minisci, Edmondo ; Vasile, M.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Univ. of Strathclyde, Glasgow, UK
Abstract :
In this paper, an adaptive version of Inflationary Differential Evolution is presented and tested on a set of real case problems taken from the CEC2011 competition on real-world applications. Inflationary Differential Evolution extends standard Differential Evolution with both local and global restart procedures. The proposed adaptive algorithm utilizes a probabilistic kernel based approach to automatically adapt the values of both the crossover and step parameters. In addition the paper presents a sensitivity analysis on the values of the parameters controlling the local restart mechanism and their impact on the solution of one of the hardest problems in the CEC2011 test set.
Keywords :
evolutionary computation; probability; sensitivity analysis; CEC2011 competition; adaptive inflationary differential evolution; crossover parameter; global restart procedure; local restart procedure; probabilistic kernel based approach; sensitivity analysis; step parameter; Algorithm design and analysis; Computer aided software engineering; Kernel; Optimization; Sociology; Standards; Statistics;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900587