61 citations · 242 across the 48 of their papers we have counts for
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Computing Diverse Sets of Solutions for Monotone Submodular Optimisation Problems
Aneta Neumann, Jakob Bossek, Frank Neumann
Submodular functions allow to model many real-world optimisation problems. This paper introduces approaches for computing diverse sets of high quality solutions for submodular opti…
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions
Jakob Bossek, Aneta Neumann, Frank Neumann
The Traveling Salesperson Problem (TSP) is one of the best-known combinatorial optimisation problems. However, many real-world problems are composed of several interacting componen…
Optimizing Monotone Chance-Constrained Submodular Functions Using Evolutionary Multi-Objective Algorithms
Aneta Neumann, Frank Neumann
Many real-world optimization problems can be stated in terms of submodular functions. Furthermore, these real-world problems often involve uncertainties which may lead to the viola…
Specific Single- and Multi-Objective Evolutionary Algorithms for the Chance-Constrained Knapsack Problem
Yue Xie, Aneta Neumann, Frank Neumann
The chance-constrained knapsack problem is a variant of the classical knapsack problem where each item has a weight distribution instead of a deterministic weight. The objective is…
Single- and Multi-Objective Evolutionary Algorithms for the Knapsack Problem with Dynamically Changing Constraints
Vahid Roostapour, Aneta Neumann, Frank Neumann
Evolutionary algorithms are bio-inspired algorithms that can easily adapt to changing environments. Recent results in the area of runtime analysis have pointed out that algorithms…
Evolving Diverse Sets of Tours for the Travelling Salesperson Problem
Anh Viet Do, Jakob Bossek, Aneta Neumann +1
Evolving diverse sets of high quality solutions has gained increasing interest in the evolutionary computation literature in recent years. With this paper, we contribute to this ar…
Evolutionary Image Transition and Painting Using Random Walks
Aneta Neumann, Bradley Alexander, Frank Neumann
We present a study demonstrating how random walk algorithms can be used for evolutionary image transition. We design different mutation operators based on uniform and biased random…
Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives
Hirad Assimi, Oscar Harper, Yue Xie +2
Real-world combinatorial optimization problems are often stochastic and dynamic. Therefore, it is essential to make optimal and reliable decisions with a holistic approach. In this…