  Cooperative coevolutionary algorithms (CCEAs) divide a given problem in to a
number of subproblems and use an evolutionary algorithm to solve each
subproblem. This short paper is concerned with the scenario under which only a
single, global fitness measure exists. By removing the typically used
subproblem partnering mechanism, it is suggested that such CCEAs can be viewed
as making use of a generalised version of the global crossover operator
introduced in early Evolution Strategies. Using the well-known NK model of
fitness landscapes, the effects of varying aspects of global crossover with
respect to the ruggedness of the underlying fitness landscape are explored.
Results suggest improvements over the most widely used form of CCEAs, something
further demonstrated using other well-known test functions.
