Affiliations: [a] Department of EE, China Jiliang University, Hangzhou, Zhejiang, China | [b] College of EE, Zhejiang University, Hangzhou, Zhejiang, China
Correspondence:
[*]
Corresponding author; Shiyou Yang, Department of EE, China Jiliang University, Hangzhou 310018, Zhejiang, China. Fax: +86 571 8795 1625; E-mail:eesyyang@zju.edu.cn
Abstract: Multi-objective design is very common in electrical
engineering, and the development of new multi-objective optimizers becomes
recently a topical issue in computational electromagnetics because of the
unavailability of a universal multi-objective optimizer. In this regard, an
improved physical programming (PP) method is presented to solve
multi-objective electromagnetic inverse problems. The improvements include: (1) the multi-pseudo preference concept is introduced to overcome the
deficiency of existing PP method in finding only one Pareto solution in a
simulation and enhance the usage rate of sampling points; (2) a novel
dynamically guiding mechanism is proposed to improve the computational
efficiency and to provide the evolutionary direction; (3) some new rules for
algorithm parameter updating are proposed to realize the two ultimate goals
of an idea multi-objective optimizer of finding as many as possible Pareto
optimal solutions and having them uniformly distributed on the Pareto Front.
The results of typical mathematic test functions and a practical
optimization design demonstrate the validity and advantages of the proposed
method.
