Yield Optimization using Hybrid Gaussian Process Regression and a Genetic Multi-Objective Approach

Quantification and minimization of uncertainty is an important task in the design of electromagnetic devices, which comes with high computational effort. We propose a hybrid approach combining the reliability and accuracy of a Monte Carlo analysis with the efficiency of a surrogate model based on Gaussian Process Regression. We present two optimization approaches. An adaptive Newton-MC to reduce the impact of uncertainty and a genetic multi-objective approach to optimize performance and robustness at the same time. For a dielectrical waveguide, used as a benchmark problem, the proposed methods outperform classic approaches.

Numerical Simulation of Acoustic Scattering by a Cylinder Based on the Enhanced Optimized Scheme

The enhanced optimized scheme we developed in the early work is employed to simulate the scattering of acoustic waves from a two-dimensional cylinder by solving the Euler equations. The numerical results of a benchmark problem are found to be in excellent agreement with the exact solution. Our numerical results show that when acoustic waves propagate through a cylinder, the acoustic scattering results in a spatial redistribution of the acoustic energy as well as an alteration of the phase of the waves. The directivities of the scattered fields change significantly for the different length ratios of acoustic wavelength to the radius of the cylinder.

Design Optimization of Wearable Multiband Antenna Using Evolutionary Algorithm Tuned with Dipole Benchmark Problem

In this paper we present the optimal design of wearable four band antenna that is suitable to work in the fifth-generation wireless systems as well as in cellular systems and in unlicensed bands. The design of the antenna relies on a careful study of optimization algorithms that are suitable for antenna design. We have proposed a benchmark problem to compare different optimization algorithms. It is the space of voltage standing wave ratio and the gain of dipole antenna that was identified for wide range of dipole length and radius. Using this pre-calculated data, we have tuned the parameters of optimization routine for optimal performance with our benchmark. After this, we optimized the geometry of four-band wearable antenna. In the optimization process, we used finite-difference time-domain method together with simplified model of human body. The antenna design was assessed with a fabricated prototype.

The Traveling Tournament Problem with Maximum Tour Length Two: A Practical Algorithm with An Improved Approximation Bound

The Traveling Tournament Problem is a well-known benchmark problem in tournament timetabling, which asks us to design a schedule of home/away games of n teams (n is even) under some feasibility requirements such that the total traveling distance of all the n teams is minimized. In this paper, we study TTP-2, the traveling tournament problem where at most two consecutive home games or away games are allowed, and give an effective algorithm for n/2 being odd. Experiments on the well-known benchmark sets show that we can beat previously known solutions for all instances with n/2 being odd by an average improvement of 2.66%. Furthermore, we improve the theoretical approximation ratio from 3/2+O(1/n) to 1+O(1/n) for n/2 being odd, answering a challenging open problem in this area.