Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

This paper contains a modern vision of the parallelization techniques used for evolutionary
algorithms (EAs). The work is motivated by two fundamental facts: 1) the different families of …

This article focuses on the formulation, validation and application of the continuous adjoint
method for turbulent flows in aero/hydrodynamic optimization. Though discrete adjoint has …

With the pressing regulatory requirement to increase energy efficiency in our built
environment, significant researching efforts have been recently directed towards energy …

The field of evolutionary computation (EC) can no longer be considered an esoteric one.
Today, after about thirty years of research, a rich corpus of theory exists and many …

Develo** multiobjective evolutionary algorithms (MOEAs) involves thoroughly addressing
the issues of efficiency and effectiveness. Once convinced of an MOEA's effectiveness the …

The high computational cost of complex engineering optimization problems has motivated
the development of parallel optimization algorithms. A recent example is the parallel particle …

One of the main reasons for using parallel evolutionary algorithms (PEAs) is to obtain
efficient algorithms with an execution time much lower than that of their sequential …

20 years in conception and 15 in construction, the SpiNNaker project has delivered the
world's largest neuromorphic computing platform incorporating over a million ARM mobile …

In this paper, we present an efficient Hierarchical Parallel Genetic Algorithm framework
using Grid computing (GE-HPGA). The framework is developed using standard Grid …