Title :
Differential evolution with automatic parameter configuration for solving the CEC2013 competition on Real-Parameter Optimization
Author :
Elsayed, Saber M. ; Sarker, Ruhul A. ; Ray, Tapabrata
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
Abstract :
The performance of Differential Evolution (DE) algorithms is known to be highly dependent on its search operators and control parameters. The selection of the parameter values is a tedious task. In this paper, a DE algorithm is proposed that configures the values of two parameters (amplification factor and crossover rate) automatically during its course of evolution. For this purpose, we considered a set of values as input for each of the parameters. The algorithm has been applied to solve a set of test problems introduced in IEEE CEC´2013 competition. The results of the test problems are compared with the known best solutions and the approach can be applied to other population based algorithms.
Keywords :
evolutionary computation; optimisation; DE algorithm; IEEE CEC2013 Competition; amplification factor; automatic parameter configuration; control parameters; crossover rate; differential evolution; population based algorithms; real-parameter optimization; search operators; Algorithm design and analysis; Equations; Gaussian distribution; Optimization; Sociology; Statistics; Vectors; differential evolution; parameter configuration;
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
DOI :
10.1109/CEC.2013.6557795
