61 citations · 115 across the 6 of their papers we have counts for
6 papers
Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem
Vahid Roostapour, Jakob Bossek, Frank Neumann
Evolutionary algorithms (EAs) are general-purpose problem solvers that usually perform an unbiased search. This is reasonable and desirable in a black-box scenario. For combinatori…
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…
Runtime Analysis of RLS and (1+1) EA for the Dynamic Weighted Vertex Cover Problem
Mojgan Pourhassan, Vahid Roostapour, Frank Neumann
In this paper, we perform theoretical analyses on the behaviour of an evolutionary algorithm and a randomised search algorithm for the dynamic vertex cover problem based on its dua…
Analysis of Baseline Evolutionary Algorithms for the Packing While Travelling Problem
Vahid Roostapour, Mojgan Pourhassan, Frank Neumann
The performance of base-line Evolutionary Algorithms (EAs) on combinatorial problems has been studied rigorously. From the theoretical viewpoint, the literature extensively investi…
Pareto Optimization for Subset Selection with Dynamic Cost Constraints
Vahid Roostapour, Aneta Neumann, Frank Neumann +1
We consider the subset selection problem for function with constraint bound that changes over time. Within the area of submodular optimization, various greedy approaches ar…
Analysis of Evolutionary Algorithms in Dynamic and Stochastic Environments
Vahid Roostapour, Mojgan Pourhassan, Frank Neumann
Many real-world optimization problems occur in environments that change dynamically or involve stochastic components. Evolutionary algorithms and other bio-inspired algorithms have…