While standard evolutionary algorithms employ a static, absolute fitness metric, co-
evolutionary algorithms assess individuals by their performance relative to populations of …

Layout design of spacecraft module belongs to scheme design problem, which has been
proved to be NP hard. This problem has not only computing complexity but also engineering …

The design and development of an Interactive Evolutionary Computation (IEC) system
needs to take into account the implementation issues found when delivering the system to" …

The execution process of an evolutionary algorithm typically involves some trial and error.
This is due to the difficulty in setting the initial parameters of the algorithm—especially when …

This research explores substitution of the fittest (SF), a technique designed to counteract the
problem of disengagement in two-population competitive coevolutionary genetic algorithms …

Given that evolutionary biologists have considered coevolutionary interactions since the
dawn of Darwinism, it is perhaps surprising that coevolution was largely overlooked during …

A novel approach for the autonomous virulence adaptation (AVA) of competing populations
in a coevolutionary optimization framework is presented. Previous work has demonstrated …

Using a multi-agent social simulation model to predict the behavior of cloud computing
markets, Rogers & Cliff (R&C) demonstrated the existence of a profitable cloud brokerage …

Coevolutionary optimisation suffers from a series of problems that interfere with the
progressive escalating arms races that are hoped might solve difficult classes of optimisation …

Coupling conventional controller design methods, model based controller synthesis and
simulation, and multi-objective evolutionary optimisation methods frequently results in an …