activity
20222024
most citedRigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems

8 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NE20241 cited

Evolutionary Multi-Objective Diversity Optimization

Anh Viet Do, Mingyu Guo, Aneta Neumann +1

Creating diverse sets of high quality solutions has become an important problem in recent years. Previous works on diverse solutions problems consider solutions' objective quality…

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.AI20238 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.NE2022

Analysis of Quality Diversity Algorithms for the Knapsack Problem

Adel Nikfarjam, Anh Viet Do, Frank Neumann

Quality diversity (QD) algorithms have been shown to be very successful when dealing with problems in areas such as robotics, games and combinatorial optimization. They aim to maxi…