An new efficient evolutionary approach for dynamic optimization problems - Liang Yong

To improve the efficiency of the currently known evolutionary algorithms for dynamic optimization problems, we have proposed a novel 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 three real-valued vectors (x,¿,r)¿ R n × R n × 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), the second vector describes the search step of x, while the third vector r represents the dynamic fitness value and the dynamic tendency of the individual x in the dynamic environment. ¿ and r are the control variables (also called strategy variables), which allow self-adaptation. The object variable vector x is operated by different genetic strategies according to its corresponding …