Frank Neumann

This paper provides new runtime results and experimental investigations for evolutionary multi-objective algorithms on the multi-objective minimum spanning tree problem.

This paper investigates the benefits of generating multiple solutions in each generation for Evolutionary Diversity Optimisation (EDO) and proposes efficient methods to achieve it.

This paper demonstrates that treewidth dynamic programming (TDP) can be used to enhance the performance of various graph combinatorial optimization algorithms.

This paper introduces an uncertainty quantification Quality Diversity framework for reliable time-use recommendations, using a large child cohort dataset and compositional data analysis.