In advanced conifer breeding programmes, the simultaneous genetic improvement of adversely correlated traits constitutes a major challenge. Population subdivision strategies have been proposed to deal with breeding objective uncertainty, to reduce inbreeding depression in production populations and to reduce genetic correlation adversity. We used Monte Carlo simulations based on a finite locus model to study the effect of a two-breeding-population strategy applying selection for each trait in each breeding population on the genetic correlation and on genetic gains in breeding populations (BP) and the production population (PP) within a time frame of ten generations. A single-BP and a two-subline strategy both applying multitrait index selection with equal trait weights were used as references. Two BP strategy simulations indicated that simultaneous genetic gain for the two traits could be achieved in the PP despite adverse pleiotropy. The adversity of the genetic correlations decreased in BPs of the two-BP strategy, in contrast to single-BP and subline strategies, but the adversity reduction came at the cost of a lower rate of aggregated (summed) genetic gain in the PP for the two-BP strategy compared to the single-BP or subline strategies. The subline strategy exhibited increased genetic gain in the PP at equal levels of inbreeding as intended. Two BP strategies could be useful to develop breeds specialised on different traits and to simultaneously reduce adverse genetic correlations. However, if the aggregated genetic gain should be maximised, the single-BP strategy appears a better choice.