activity
20102024
most citedPareto Optimization for Subset Selection with Dynamic Cost Constraints

61 citations · 570 across the 108 of their papers we have counts for

collaborators

114 papers

cs.NE2024

Fixed-Parameter Tractability of the (1+1) Evolutionary Algorithm on Random Planted Vertex Covers

Jack Kearney, Frank Neumann, Andrew M. Sutton

We present the first parameterized analysis of a standard (1+1) Evolutionary Algorithm on a distribution of vertex cover problems. We show that if the planted cover is at most loga…

math.OC2023

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…

cs.DS2023

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…

cs.NE2023★ 1 cited

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…

cs.AI2023★ 8 cited

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…

cs.NE2023★ 1 cited

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…