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Generic Postprocessing via Subset Selection for Hypervolume and Epsilon-Indicator
Two generic postprocessing algorithms are presented which utilize the archive of all non-dominated solutions evaluated during the search to choose the best μ solutions from the archive such that the hypervolume or e-indicator is maximized. Expand
Two-dimensional subset selection for hypervolume and epsilon-indicator
This work presents a new algorithm for the hypervolume SSP with runtime O(n (k + log n) + m log m) and a new algorithms for the ε-indicator SSPwith runtime O (n log n + mlog m) that improve the current state of the art runtimes by a factor of (nearly) $n and make the problems tractable for new applications. Expand
A General Framework for Dynamic Succinct and Compressed Data Structures
This paper design, implement, and test a general framework that allows for practical dynamic succinct structures, and describes implementations of compressed modifiable bit vectors, and extended compressed random access memory. Expand
Efficient computation of two-dimensional solution sets maximizing the epsilon-indicator
A new algorithm is presented with runtime O(k · log2(δ-1)), which is an exponential improvement regarding the dependence on the error δ compared to all previous work, and optimal solution sets for sets of cardinality k are determined. Expand