  This paper is a short report about our work for the primal task in the
Machine Learning for Combinatorial Optimization NeurIPS 2021 Competition. For
each dataset of our interest in the competition, we propose customized primal
heuristic methods to efficiently identify high-quality feasible solutions. The
computational studies demonstrate the superiority of our proposed approaches
over the competitors'.
