In this paper two classes of iterative methods for saddle point problems are considered: inexact Uzawa algorithms and a class of methods with symmetric preconditioners. In both cas...
Conventional autotuning configuration of parameters in distributed computing systems using evolutionary strategies increases integrated performance notably, though at the expense ...
There exist a number of high-performance Multi-Objective Evolutionary Algorithms (MOEAs) for solving MultiObjective Optimization (MOO) problems; two of the best are NSGA-II and -M...
Matt D. Johnson, Daniel R. Tauritz, Ralph W. Wilke...
When requirements models are developed in an iterative and evolutionary way, requirements validation becomes a major problem. In order to detect and fix problems early, the speci...
Optimal constellation design is important in military digital communications for Quadrature Amplitude Modulation (QAM). Optimization realizes a reduced probability of bit error (P...