6 citations · 14 across the 18 of their papers we have counts for
5 papers · 1 filter
Theoretical Analysis of Quality Diversity Algorithms for a Classical Path Planning Problem
Duc-Cuong Dang, Aneta Neumann, Frank Neumann +2
Quality diversity (QD) algorithms have shown to provide sets of high quality solutions for challenging problems in robotics, games, and combinatorial optimisation. So far, theoreti…
Many Objective Problems Where Crossover is Provably Essential
Andre Opris
This article addresses theory in evolutionary many-objective optimization and focuses on the role of crossover operators. The advantages of using crossover are hardly understood an…
Illustrating the Efficiency of Popular Evolutionary Multi-Objective Algorithms Using Runtime Analysis
Duc-Cuong Dang, Andre Opris, Dirk Sudholt
Runtime analysis has recently been applied to popular evolutionary multi-objective (EMO) algorithms like NSGA-II in order to establish a rigorous theoretical foundation. However, m…
Runtime Analyses of NSGA-III on Many-Objective Problems
Andre Opris, Duc-Cuong Dang, Frank Neumann +1
NSGA-II and NSGA-III are two of the most popular evolutionary multi-objective algorithms used in practice. While NSGA-II is used for few objectives such as 2 and 3, NSGA-III is des…
Achieving Tight Runtime Bounds on Jump by Proving that Genetic Algorithms Evolve Near-Maximal Population Diversity
Andre Opris, Johannes Lengler, Dirk Sudholt
The JUMP benchmark was the first problem for which crossover was proven to give a speed-up over mutation-only evolutionary algorithms. Jansen and Wegener (2002) proved an upper…