61 citations · 570 across the 108 of their papers we have counts for
10 papers · 1 filter
Automated Algorithm Selection: Survey and Perspectives
Pascal Kerschke, Holger H. Hoos, Frank Neumann +1
It has long been observed that for practically any computational problem that has been intensely studied, different instances are best solved using different algorithms. This is pa…
Evolutionary Diversity Optimization Using Multi-Objective Indicators
Aneta Neumann, Wanru Gao, Markus Wagner +1
Evolutionary diversity optimization aims to compute a diverse set of solutions where all solutions meet a given quality criterion. With this paper, we bridge the areas of evolution…
Pareto Optimization for Subset Selection with Dynamic Cost Constraints
Vahid Roostapour, Aneta Neumann, Frank Neumann +1
We consider the subset selection problem for function with constraint bound that changes over time. Within the area of submodular optimization, various greedy approaches ar…
Greedy Maximization of Functions with Bounded Curvature under Partition Matroid Constraints
Tobias Friedrich, Andreas Göbel, Frank Neumann +2
We investigate the performance of a deterministic GREEDY algorithm for the problem of maximizing functions under a partition matroid constraint. We consider non-monotone submodular…
Analysis of Evolutionary Algorithms in Dynamic and Stochastic Environments
Vahid Roostapour, Mojgan Pourhassan, Frank Neumann
Many real-world optimization problems occur in environments that change dynamically or involve stochastic components. Evolutionary algorithms and other bio-inspired algorithms have…
Design and Analysis of Diversity-Based Parent Selection Schemes for Speeding Up Evolutionary Multi-objective Optimisation
Edgar Covantes Osuna, Wanru Gao, Frank Neumann +1
Parent selection in evolutionary algorithms for multi-objective optimisation is usually performed by dominance mechanisms or indicator functions that prefer non-dominated points. W…