Decomposition and cooperative coevolution techniques for large scale global optimization
Xiaodong Li · 2014
Many real-world optimization problems involve a large number of decision variables. For example, in shape optimization a large number of shape design variables are often used to represent complex shapes, such as turbine blades, aircraft wings, and heat exchangers. However, existing optimization methods are ill-equipped in dealing with this sort of large scale global optimization (LSGO) problems. A natural approach to tackle LSGO problems is to adopt a divide-and-conquer strategy. A good example is the early work on a cooperative coevolutionary (CC) algorithm by Potter and De Jong (1994), where a problem is decomposed into several subcomponents of smaller sizes, and then each subcomponent is "cooperatively coevolved" with other subcomponents.