Cooperative Co-evolution (CC) is a promising framework for solving large-scale optimization problems. However, the round-robin strategy of CC leads to its low efficiency for allocating the available computational resources to subcomponents of imbalanced functions. Contribution Based Cooperative Co-evolution (CBCC) is a variant of CC that allocates the available computational resources to the subcomponents based on their contributions, but its efficiency relies on the contribution and it allocates resources in a static way. In this paper, we proposed an improved contribution based CC with adaptive computational resource allocation (ICCC). This approach revises the calculation of contribution using evolution path to calculate the contribution. To increase evolutionary diversity, ICCC dynamically allocates computational resources to subcomponents. Experiments conduct on CEC’2010 and CEC’2013 LSGO benchmark function. The experimental results confirm that ICCC is significantly better than any other method.