Towards an automated innovization method for handling discrete search spaces

Following manual observation of hidden relationships present in Pareto-optimal (PO) solutions of a multi-objective optimization problem, an automated Innovization procedure was suggested earlier for extracting innovative design principles. The goal was to obtain closed form and simple to understand relations that exist among PO solutions in a design or other problems. The proposed automated Innovization method was developed for handling continuous variable spaces. Since, most practical design problems have discrete variables in their descriptions, the aim of this study is to extend the earlier automated Innovization procedure to handle discrete variable spaces. We discuss the difficulties posed to an automated procedure due to the search space granularity and demonstrate the working of our proposed method on one numerical problem and two engineering design problems. Our study amply demonstrates that the extension of a real-parameter automated Innovization is not straightforward to discrete spaces, however such a procedure for discrete spaces raises new challenges which must be addressed for handling problems with mixed continuous-discrete search space problems.