61 citations · 242 across the 48 of their papers we have counts for
51 papers
Taming Treewidth DP with Modulators: A General Booster for Graph Heuristics
Jialiang Li, Aneta Neumann, Frank Neumann +2
Treewidth is a fundamental graph invariant that quantifies how tree-like a given graph is. It is extensively used with dynamic programming to design fixed-parameter tractable algor…
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…
Improving Confidence in Evolutionary Mine Scheduling via Uncertainty Discounting
Michael Stimson, William Reid, Aneta Neumann +2
Mine planning is a complex task that involves many uncertainties. During early stage feasibility, available mineral resources can only be estimated based on limited sampling of ore…
Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems
Diksha Goel, Aneta Neumann, Frank Neumann +2
We study a Stackelberg game between one attacker and one defender in a configurable environment. The defender picks a specific environment configuration. The attacker observes the…
Fixed Parameter Multi-Objective Evolutionary Algorithms for the W-Separator Problem
Samuel Baguley, Tobias Friedrich, Aneta Neumann +3
Parameterized analysis provides powerful mechanisms for obtaining fine-grained insights into different types of algorithms. In this work, we combine this field with evolutionary al…
Evolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits
Kokila Perera, Aneta Neumann, Frank Neumann
Evolutionary multi-objective algorithms have been widely shown to be successful when utilized for a variety of stochastic combinatorial optimization problems. Chance constrained op…
Towards Self-adaptive Mutation in Evolutionary Multi-Objective Algorithms
Furong Ye, Frank Neumann, Jacob de Nobel +2
Parameter control has succeeded in accelerating the convergence process of evolutionary algorithms. While empirical and theoretical studies have shed light on the behavior of algor…
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler
Frank Neumann, Aneta Neumann, Chao Qian +7
Submodular functions play a key role in the area of optimization as they allow to model many real-world problems that face diminishing returns. Evolutionary algorithms have been sh…
Limited Query Graph Connectivity Test
Mingyu Guo, Jialiang Li, Aneta Neumann +2
We propose a combinatorial optimisation model called Limited Query Graph Connectivity Test. We consider a graph whose edges have two possible states (On/Off). The edges' states are…
Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs
Mingyu Guo, Max Ward, Aneta Neumann +2
Active Directory (AD) is the default security management system for Windows domain networks. An AD environment naturally describes an attack graph where nodes represent computers/a…
Computing High-Quality Solutions for the Patient Admission Scheduling Problem using Evolutionary Diversity Optimisation
Adel Nikfarjam, Amirhossein Moosavi, Aneta Neumann +1
Diversification in a set of solutions has become a hot research topic in the evolutionary computation community. It has been proven beneficial for optimisation problems in several…
Evolutionary Time-Use Optimization for Improving Children's Health Outcomes
Yue Xie, Aneta Neumann, Ty Stanford +3
How someone allocates their time is important to their health and well-being. In this paper, we show how evolutionary algorithms can be used to promote health and well-being by opt…
Evolutionary Algorithms for Limiting the Effect of Uncertainty for the Knapsack Problem with Stochastic Profits
Aneta Neumann, Yue Xie, Frank Neumann
Evolutionary algorithms have been widely used for a range of stochastic optimization problems in order to address complex real-world optimization problems. We consider the knapsack…
Coevolutionary Pareto Diversity Optimization
Aneta Neumann, Denis Antipov, Frank Neumann
Computing diverse sets of high quality solutions for a given optimization problem has become an important topic in recent years. In this paper, we introduce a coevolutionary Pareto…
Evolutionary Diversity Optimisation for The Traveling Thief Problem
Adel Nikfarjam, Aneta Neumann, Frank Neumann
There has been a growing interest in the evolutionary computation community to compute a diverse set of high-quality solutions for a given optimisation problem. This can provide th…
Defending Active Directory by Combining Neural Network based Dynamic Program and Evolutionary Diversity Optimisation
Diksha Goel, Max Ward, Aneta Neumann +3
Active Directory (AD) is the default security management system for Windows domain networks. We study a Stackelberg game model between one attacker and one defender on an AD attack…
Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson Problem
Anh Viet Do, Mingyu Guo, Aneta Neumann +1
In this work, we consider the problem of finding a set of tours to a traveling salesperson problem (TSP) instance maximizing diversity, while satisfying a given cost constraint. Th…
Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs
Mingyu Guo, Jialiang Li, Aneta Neumann +2
Active Directory is the default security management system for Windows domain networks. We study the shortest path edge interdiction problem for defending Active Directory style at…
On the Use of Quality Diversity Algorithms for The Traveling Thief Problem
Adel Nikfarjam, Aneta Neumann, Frank Neumann
In real-world optimisation, it is common to face several sub-problems interacting and forming the main problem. There is an inter-dependency between the sub-problems, making it imp…
Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation
Adel Nikfarjam, Jakob Bossek, Aneta Neumann +1
Evolutionary algorithms based on edge assembly crossover (EAX) constitute some of the best performing incomplete solvers for the well-known traveling salesperson problem (TSP). Oft…