Intelligent selection of parents for mutation in differential evolution

In most DE algorithms, the parents for mutation are randomly selected from the current population, which will mean that all vectors involved in mutation are equally selected as parents without any selection pressure. Although such a mutation strategy is easy to use, it is inefficient for solving complex problems. To address this issue, we present an intelligent parents selection strategy (IPS) for DE. The new algorithmic framework is named as DE with IPS-based mutation (IPSDE). In IPSDE, the neighbourhood of each individual is firstly constructed with a population topology. Then, all the neighbours of each individual are partitioned into two groups based on their fitness values and a probability value for each neighbour is selected as the parents in the respective groups are calculated based on its distance from the current individual. With the probability values, IPS selects the parents from the neighbourhood of the current individual to guide the mutation process of DE. To evaluate the effectiveness of the proposed approach, IPSDE is applied to several original DE algorithms and advanced DE variants. Experimental results have shown that IPSDE is an effective framework to enhance the performance of most DE algorithms studied.