  In this paper, we present a significant improvement of Quick Hypervolume
algorithm, one of the state-of-the-art algorithms for calculating exact
hypervolume of the space dominated by a set of d-dimensional points. This value
is often used as a quality indicator in multiobjective evolutionary algorithms
and other multiobjective metaheuristics and the efficiency of calculating this
indicator is of crucial importance especially in the case of large sets or many
dimensional objective spaces. We use a similar divide and conquer scheme as in
the original Quick Hypervolume algorithm, but in our algorithm we split the
problem into smaller sub-problems in a different way. Through both theoretical
analysis and computational study we show that our approach improves
computational complexity of the algorithm and practical running times.
