Cross-fertilization vs. Collaboration in Simulations of Open Innovation

Abstract

Evolutionary models allow us to approach innovation by the means of computer simulation with genetic algorithms. Open innovation can be considered in these models in different ways. A popular model by David Goldberg connects re-combinations of elements during evolutionary processes with the exchange of information in cross-fertilization activities. Another possibility is to model the collaboration of contributors with specific skills and experiences through sophisticated change operators that work systematically on improvements with respect to certain aspects of the innovation context. A simulation of this procedure on an instance of the permutation flow shop scheduling problem shows that the usage of these operators can indeed increase the performance of the solution generation, if certain constraints are kept in consideration.