Self-adaptive parameterization using 3-parents differential evolution
Teng Nga Sing, Jason Teo, Mohd Hanafi Ahmad Hijazi · International MultiConference of Engineers and Computer Scientists · 2007
The aim of 3-Parents Differential Evolution (3PDE) is to reduce the parental requirement in the original Differential Evolution (DE). The effectiveness of 3PDE has been reported and is considered as a useful algorithm that performed better convergence to optimality. In general, 3PDE is considered as a useful contribution since it has successfully reduced the parental requirement in DE without significant reductions in absolute optimization performance by gaining better average performance as well as stability. The objective of this paper is to investigate whether certain parameters that are self-adapted in 3PDE can enhance its performance for function optimization. Here, we propose three new algorithms to compare against 3PDE for their performance, which included 3SACr, 3SAF, and 3SAFCr. Fifty run were conducted for each 20 well-known benchmark functions to test all proposed algorithms. The experimental results showed that 3SACr performed the best among the other algorithms in terms of its better average performance as well stability.