Parallel constraint handling in a multiobjective evolutionary algorithm for the automotive deployment problem

The component deployment problem is a complex multiobjective optimisation task faced by engineers in the automotive industry. Thus far, the best-known solutions to this problem have been achieved using the NSGA-II algorithm combined with a constraint handling method based on repairing solutions that have been rendered infeasible by the genetic operators. It can reasonably be assumed that an approach that repairs solutions immediately after a change has limited coverage of the infeasible space. Exchanging solutions with other algorithms may help enhance the search space coverage. However, we observe an improvement in performance through parallelisation only after increasing the complexity of the problem.