Review of Knowledge Guidance in Intelligent Optimization Approaches

The interaction between learning and evolution has recently become a popular research direction. Many scholars make use of knowledge to strengthen the guidance process in intelligent optimization methods. We review knowledge guidance in intelligent optimization approaches, which is normally carried out through artificial intelligence approaches and special knowledge models. Some researchers have also proposed algorithms with a double-layer evolution mechanism. These improved methods are able to discover some knowledge from previous iterations and to use the discovered knowledge to guide subsequent iterations.