
arXiv: 1510.01963
We propose a new approach to the computation of the hypervolume indicator, based on partitioning the dominated region into a set of axis-parallel hyperrectangles or boxes. We present a nonincremental algorithm and an incremental algorithm, which allows insertions of points, whose time complexities are $O(n^{\lfloor \frac{p-1}{2} \rfloor+1})$ and $O(n^{\lfloor \frac{p}{2} \rfloor+1})$, respectively. While the theoretical complexity of such a method is lower bounded by the complexity of the partition, which is, in the worst-case, larger than the best upper bound on the complexity of the hypervolume computation, we show that it is practically efficient. In particular, the nonincremental algorithm competes with the currently most practically efficient algorithms. Finally, we prove an enhanced upper bound of $O(n^{p-1})$ and a lower bound of $��(n^{\lfloor \frac{p}{2}\rfloor} \log n )$ for $p \geq 4$ on the worst-case complexity of the WFG algorithm.
21 pages
FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Integer programming, multi-objective optimization, Numerical aspects of computer graphics, image analysis, and computational geometry, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), Multi-objective and goal programming, hypervolume indicator, Klee's measure problem, Computer Science - Discrete Mathematics
FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Integer programming, multi-objective optimization, Numerical aspects of computer graphics, image analysis, and computational geometry, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), Multi-objective and goal programming, hypervolume indicator, Klee's measure problem, Computer Science - Discrete Mathematics
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