Surrogate-Assisted Evolutionary Framework for Data-Driven Dynamic Optimization
Wenjian Luo, Ruikang Yi, Bin Yang, Peilan Xu · IEEE Transactions on Emerging Topics in Computational Intelligence · 2018
Recently, dynamic optimization has received much attention from the swarm and evolutionary computation community. However, few studies have investigated data-driven evolutionary dynamic optimization, and most algorithms for evolutionary dynamic optimization are based on analytical mathematical functions. In this paper, we investigate data-driven evolutionary dynamic optimization. First, we develop a surrogate-assisted evolutionary framework for solving data-driven dynamic optimization problems (DD-DOPs). Second, we employ a benchmark based on the typical dynamic optimization problems set in order to verify the performance of the proposed framework. The experimental results demonstrate that the proposed framework is effective for solving DD-DOPs.