Title :
Preserving rotation invariant properties in differential evolution algorithm
Author :
Alam Anik, Tanvir ; Md Noman, Abu Saleh ; Ahmed, Shehab
Author_Institution :
Dept. of Comput. Sci. & Eng. (CSE), Bangladesh Univ. of Eng. & Technol. (BUET), Dhaka, Bangladesh
Abstract :
Differential evolution (DE) is an efficient and powerful population-based stochastic direct search method for solving optimization problems over continuous space. It uses both crossover and mutation for producing offspring. Mutation is rotation-invariant while crossover is not rotation-invariant. As a result, the performance of DE degrades in problems with strong linkage among variables. In this paper, we propose a new DE algorithm that uses rotation-invariant crossover operators to achieve better optimization performance when solving rotated problems. The proposed algorithm has been examined on a test-suite of 12 benchmark functions. Experimental results have demonstrated the effectiveness of the proposed algorithm.
Keywords :
evolutionary computation; mathematical operators; optimisation; search problems; stochastic processes; DE algorithm; benchmark functions; continuous space; differential evolution algorithm; optimization performance; optimization problems; population-based stochastic direct search method; rotation invariant properties; rotation-invariant crossover operators; Benchmark testing; Couplings; Iron; Optimization; Sociology; Statistics; Vectors; Gram-Schmidt process; KEY WORDS; Rotation-invariant; crossover; differential evolution; function optimization; mutation;
Conference_Titel :
Advances in Electrical Engineering (ICAEE), 2013 International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4799-2463-9
DOI :
10.1109/ICAEE.2013.6750339