Abstract
A kriging-assisted light beam search (LBS) method is proposed to solve multi-objective inverse problems. To reduce the computational burden and increase the convergence speed, a kriging model is introduced into the evolutionary procedure of the LBS method. To guarantee the accuracy of the final Pareto solutions, a dynamic detecting strategy is used in the LBS method. To reflect the preference of a decision maker (DM) in decision making, a boundary control mechanism is proposed to assure that all the obtained Pareto solutions are well-distributed within the preference of the DM. To testify the accuracy of the proposed method, a typical test function, a benchmark inverse problem, TEAM Workshop Problem 22, and a linear antenna array design are solved. The numerical results demonstrate the effectiveness and efficiency of the proposed method.
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