Does Relaxing Strict Acceptance Condition Improve Test Based Pareto Coevolution?

The strict acceptance condition between parent and child is one of the guarantees of monotonic progress in Pareto co-evolution. However, this condition results in stalling in progress especially when the cardinality of test set is as large as in the scale of population size in a test based coevolutionary algorithm. We presented two variants of Pareto based Coevolutionary Hill Climber algorithms - rP-PHC-P that relax the strict condition based on competitive shared fitness of non-comparable (parent, child) pairs and fP-PHC-P which relaxes the condition in the form of discarding Pareto dominated candidate solutions regardless of being parent or child as soon as the Pareto front is created. Both of the algorithms improve the progress, are successfully tested for avoiding overspecialization and keep less non-unique candidate solutions in the population slot compare to P-PHC-P