61 citations · 570 across the 108 of their papers we have counts for
16 papers · 1 filter
Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties
Xiankun Yan, Anh Viet Do, Feng Shi +2
Chance constraints are frequently used to limit the probability of constraint violations in real-world optimization problems where the constraints involve stochastic components. We…
Diverse Approximations for Monotone Submodular Maximization Problems with a Matroid Constraint
Anh Viet Do, Mingyu Guo, Aneta Neumann +1
Finding diverse solutions to optimization problems has been of practical interest for several decades, and recently enjoyed increasing attention in research. While submodular optim…
Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax
Denis Antipov, Aneta Neumann, Frank Neumann
The evolutionary diversity optimization aims at finding a diverse set of solutions which satisfy some constraint on their fitness. In the context of multi-objective optimization th…
Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems
Anh Viet Do, Aneta Neumann, Frank Neumann +1
We study the multi-objective minimum weight base problem, an abstraction of classical NP-hard combinatorial problems such as the multi-objective minimum spanning tree problem. We p…
On the Impact of Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem
Jakob Bossek, Aneta Neumann, Frank Neumann
Evolutionary algorithms have been shown to obtain good solutions for complex optimization problems in static and dynamic environments. It is important to understand the behaviour o…
Analysis of the (1+1) EA on LeadingOnes with Constraints
Tobias Friedrich, Timo Kötzing, Aneta Neumann +2
Understanding how evolutionary algorithms perform on constrained problems has gained increasing attention in recent years. In this paper, we study how evolutionary algorithms optim…