Design of compact microstrip lowpass elliptic filter with wide stop band using invasive weed optimization
In this paper, the invasive weed optimization technique is used to design a compact microstrip elliptic low pass filter with very high order suppression response. This method enhances the filter stop band bandwidth more than 8.5 f3dB and achieves 47% compactness compared with the traditional elliptic filter. The measurement results of the final optimized fabricated filter are in good agreement with the simulation ones.
Optimization of Printed Yagi Antenna Using Invasive Weed Optimization (IWO)
In this letter, the Invasive Weed Optimization (IWO) method is applied to design and optimize a printed Yagi antenna. The optimization goals are set to reach an antenna with a VSWR less than 1.5 and a high-gain radiation pattern. The fitness function is calculated by FEKO, which uses the method of moments for evaluating the structures. By implementing this simple closed-loop algorithm, the best available structure has been achieved compared to the results of the previous studies. Finally, a C-band optimized version of the antenna is fabricated and tested. The experimental data are in good agreement with the simulation results, which verifies the performance of the IWO method.
Hybrid simulated annealing and direct search method for nonlinear unconstrained global optimization
In this article we give a new approach of hybrid direct search methods with meta-heuristics of simulated annealing for finding a global minimum of a nonlinear function with continuous variables. First, we suggest a Simple Direct Search (SDS) method, which comes from some ideas of other well-known direct search methods. Since our goal is to find global minima and the SDS method is still a local search method, we hybridize it with the standard simulated annealing to design a new method, called Simplex Simulated Annealing (SSA) method, which is expected to have some ability to look for a global minimum. To obtain faster convergence, we first accelerate the cooling schedule in SSA, and in the final stage, we apply Kelley's modification of the Nelder-Mead method on the best solutions found by the accelerated SSA method to improve the final results. We refer to this last method as the Direct Search Simulated Annealing (DSSA) method. The performance of SSA and DSSA is reported through extensive numerical experiments on some well-known functions. Comparing their performance with that of other meta-heuristics shows that SSA and DSSA are promising in practice. Especially, DSSA is shown to be very efficient and robust.