activity
20242026
collaborators

13 papers

cs.NE2026

Insights from Multi-tasking the EAX Algorithm for the Travelling Salesperson Problem

Liam Wigney, Aneta Neumann, Yew-Soon Ong +1

Evolutionary multitasking allows several related problems to be solved in a single run of an algorithm. In this paper, we investigate integrating evolutionary multitasking with Edg…

stat.ML2026

Quality Diversity for Reliable Data Driven Time-Use Optimization

Aneta Neumann, Ty Stanford, Dorothea Dumuid +1

The daily allocation of the finite 24-hour time budget is strongly associated with physical, mental, and cognitive health. While predictive models can estimate the relationship bet…

math.OC2026

Combinatorial CAR T-cell Circuit Design using Single- and Multi-Objective Local Search

Bartol Borozan, Alice Descoeudres, Aneta Neumann +2

CAR T-cell circuit design enables targeting tumour cells while keeping healthy cells unaffected to a cancer treatment. Designing CAR T-cell circuits that maximize the number of tum…

cs.NE2026

On the Use of Survival Selection Methods for Evolutionary Diversity Optimisation

Adel Nikfarjam, Jakob Bossek, Aneta Neumann +1

Generating a diverse set of high quality solutions for an optimisation problem has been studied extensively in recent years by the evolutionary computation community. A paradigm th…

cs.DS2026

Effective Traveling for Metric Instances of the Traveling Thief Problem

Jan Eube, Kelin Luo, Aneta Neumann +2

The Traveling Thief Problem (TTP) is a multi-component optimization problem that captures the interplay between routing and packing decisions by combining the classical Traveling S…

cs.NE2025

Runtime Analysis of Evolutionary Diversity Optimization on the Multi-objective (LeadingOnes, TrailingZeros) Problem

Denis Antipov, Aneta Neumann, Frank Neumann +1

Diversity optimization is the class of optimization problems in which we aim to find a diverse set of good solutions. One of the frequently-used approaches to solve such problems i…