Extracting knowledge from solutions and then using it to guide the search is a complex task, which has not been highly explored in a discrete multi-objective optimization context. Considering the papers on that subject leads to the following terminology for Knowledge Discovery (KD) processes. A KD process is built upon two main procedures called Knowledge Extraction and Knowledge Injection. The extraction procedure aims to extract problem-related knowledge from one or several solutions.
Then the extracted knowledge can be used by the injection procedure to build new solutions taking into account past iterations.
In this article, we investigate how a KD mechanism can be integrated into MOEA/D, to solve a bi-objective Vehicle Routing Problem with Time Windows (bVRPTW).