A Study On Multiobjective Intelligent Optimization Algorithms And Applications In Antenna Designs

Practical optimization problems generally involve multiple objectives that conflict with each other. The improvement of one objective may lead to the deterioration of other ones. It is necessary to achieve the approximation to the solutions and diversity on the real Pareto front, and also high efficiency is required for the algorithm. The intrinsic complexity of multiobjective optimization problems leads to a huge increase of difficulty in finding optimal solutions. This paper studies the mechanisms and performances of excellent multiobjective optimization algorithms, such as NSGA-II. Based on the strategies of TPA, a novel algorithm for multiobjective optimization, nondominated ranking team progress algorithm(NRTPA) is proposed.The high efficiency of NRTPA in finding optimal solutions is analyzed in principle. As few offspring are generated each iteration, the number of fitness calculations decreases significantly, which contributes to the improvement of evolutionary efficiency and the acceleration of convergence. The performance is tested using ZDT and DTLZ benchmark problems, and is verified by multiobjective metrics. Numerical results show that NRTPA has the properties of fast convergence, uniform distribution and low computation cost. Thus NRTPA is valuable for practical engineering problems with high fitness computation cost, such as antenna optimization designs.Combining the optimization algorithm and simulation software by scripts to optimize the antenna design is discussed. Then NRTPA is employed to optimize a planar UWB monopole antenna. Consequently, the two objectives, minimization of |S11| over the UWB frequency band and minimization of the antenna structure area, are optimized simultaneously. The performance is further demonstrated by measuring the fabricated antenna of optimal size.Numerical results and the optimization of the UWB antenna show that NRTPA is a promising algorithm for multiobjective optimization and antenna design, and applicable to solve practical electromagnetic optimization problems.