The Tracking Dynamical Evolutionary Algorithm for Dynamic Environments

In this paper, we proposed the Tracking Dynamical Evolutionary Algorithm (TDEA) that can efficiently locate and track the optimal solution in a dynamically changing environment. In TDEA, the particle\´s structure is different from traditional DEA. Each particle\´s knowledge is applied an "evaporation constant" to gradually weaken the knowledge\´s validity. Through this mechanism, the knowledge of each particle will be gradually updated in a dynamically changing environment. Compared with the traditional DEA, TDEA can quickly converge to the area  of the goal and maintain the shortest distance from the goal.