Multi-parent crossover allows more than two parents participating in crossover. The increase of parents in crossover intensifies exploitation or exploration or both; however, the intensification is often unbalanced and consequently causes deterioration in performance. In this paper we propose the use of supermajority to address the issue of lopsided intensification on exploitation and exploration in multi-parent crossover. The proposed crossover, called biased occurrence-based scanning crossover (bOB), controls the tendency toward exploitation or exploration by the threshold in supermajority. Two adaptive strategies are developed to adjust the threshold of bOB. Experimental results indicate that bOB can achieve significant improvement on uniform crossover and occurrence- based scanning crossover in both solution quality and convergence speed. Precisely, the improvement in mean best fitness ranges from 4-89% on our test problems. The preferable results validate that bOB crossover can not only enhance the performance but also provide an effective way to control the exploitation and exploration in crossover.