A novel genetic variable representation for dynamic optimization problems in evolutionary computation - Liang Yong

This paper introduces a novel genetic variable representation for dynamic optimization problems in evolutionary computation. This variable representation allows static evolutionary optimization approaches to be extended to efficiently explore global and better local optimal areas in dynamic fitness landscapes. It represents a single individual as a pair of real-valued vector (x, r)∈ R n x R 2 in the evolutionary search population. The first vector x corresponds to a point in the n-dimensional search space (an object variable vector), while the second vector r represents the dynamic fitness value and the dynamic tendency of the individual x in the dynamic environment. r is the control variable (also called strategy variable), which allow self-adaptation. The object variable vector x is operated by different genetic strategies according to its corresponding r. As a case study, we have integrated the new variable representation …