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While the theoretical analysis of evolutionary algorithms (EAs) has made significant progress for pseudo-Boolean optimization problems in the last 25 years, only sporadic theoretical results exist on how EAs solve permutation-based…

Neural and Evolutionary Computing · Computer Science 2022-10-07 Benjamin Doerr , Yassine Ghannane , Marouane Ibn Brahim

We construct a fixed parameter algorithm parameterized by d and k that takes as an input a graph G' obtained from a d-degenerate graph G by complementing on at most k arbitrary subsets of the vertex set of G and outputs a graph H such that…

Discrete Mathematics · Computer Science 2018-06-28 Jakub Gajarsky , Daniel Kral

Constrained submodular optimization problems play a key role in the area of combinatorial optimization as they capture many NP-hard optimization problems. So far, Pareto optimization approaches using multi-objective formulations have been…

Neural and Evolutionary Computing · Computer Science 2024-06-21 Frank Neumann , Günter Rudolph

To gain a better theoretical understanding of how evolutionary algorithms (EAs) cope with plateaus of constant fitness, we propose the $n$-dimensional Plateau$_k$ function as natural benchmark and analyze how different variants of the $(1 +…

Neural and Evolutionary Computing · Computer Science 2021-11-02 Denis Antipov , Benjamin Doerr

Capacitated Vertex Cover is the hard-capacitated variant of Vertex Cover: given a graph, a capacity for every vertex, and an integer $k$, the task is to select at most $k$ vertices that cover all edges and assign each edge to one of its…

Data Structures and Algorithms · Computer Science 2026-04-22 Michael Lampis , Manolis Vasilakis

We revisit Approximate Graph Propagation (AGP), a unified framework which captures various graph propagation tasks, such as PageRank, feature propagation in Graph Neural Networks (GNNs), and graph-based Retrieval-Augmented Generation (RAG).…

Data Structures and Algorithms · Computer Science 2026-01-13 Zhuowei Zhao , Zhuo Zhang , Hanzhi Wang , Junhao Gan , Zhifeng Bao , Jianzhong Qi

Under Frequency Fitness Assignment (FFA), the fitness corresponding to an objective value is its encounter frequency in fitness assignment steps and is subject to minimization. FFA renders optimization processes invariant under bijective…

Neural and Evolutionary Computing · Computer Science 2020-10-19 Thomas Weise , Zhize Wu , Xinlu Li , Yan Chen

Evolutionary algorithms (EAs) are heuristic algorithms inspired by natural evolution. They are often used to obtain satisficing solutions in practice. In this paper, we investigate a largely underexplored issue: the approximation…

Neural and Evolutionary Computing · Computer Science 2015-03-17 Yang Yu , Xin Yao , Zhi-Hua Zhou

In a large-scale network, we want to choose some influential nodes to make a profit by paying some cost within a limited budget so that we do not have to spend more budget on some nodes adjacent to the chosen nodes; our problem is the…

Data Structures and Algorithms · Computer Science 2026-01-30 Sipra Singh

Inversion of a directed graph $D$ with respect to a vertex subset $Y$ is the directed graph obtained from $D$ by reversing the direction of every arc whose endpoints both lie in $Y$. More generally, the inversion of $D$ with respect to a…

Data Structures and Algorithms · Computer Science 2026-04-08 Dhanyamol Antony , L. Sunil Chandran , Dalu Jacob , R. B. Sandeep

The Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) is a state of the art evolutionary algorithm that leverages linkage learning to efficiently exploit problem structure. By identifying and preserving important building blocks…

Neural and Evolutionary Computing · Computer Science 2024-07-12 Yukai Qiao , Marcus Gallagher

Linear functions play a key role in the runtime analysis of evolutionary algorithms and studies have provided a wide range of new insights and techniques for analyzing evolutionary computation methods. Motivated by studies on separable…

Neural and Evolutionary Computing · Computer Science 2022-08-12 Frank Neumann , Carsten Witt

We study deterministic algorithms for computing graph cuts, with focus on two fundamental problems: balanced sparse cut and $k$-vertex connectivity for small $k$ ($k=O(\polylog n)$). Both problems can be solved in near-linear time with…

Data Structures and Algorithms · Computer Science 2019-10-21 Yu Gao , Jason Li , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak , Sorrachai Yingchareonthawornchai

The Makespan Scheduling problem is an extensively studied NP-hard problem, and its simplest version looks for an allocation approach for a set of jobs with deterministic processing times to two identical machines such that the makespan is…

Neural and Evolutionary Computing · Computer Science 2025-04-25 Feng Shi , Daoyu Huang , Xiankun Yan , Frank Neumann

This work introduces two techniques for the design and analysis of branching algorithms, illustrated through the case study of the Vertex Cover problem. First, we present a method for automatically generating branching rules through a…

Data Structures and Algorithms · Computer Science 2025-10-13 Katie Clinch , Serge Gaspers , Tao Zixu He , Simon Mackenzie , Tiankuang Zhang

We present a simple randomized algorithm that can efficiently maintain a $(\Delta+1)$ coloring as the graph undergoes edge insertion and deletion updates, where $\Delta$ denotes an upper bound on the maximum degree. A key advantage is the…

Data Structures and Algorithms · Computer Science 2025-12-11 Mohsen Ghaffari , Jaehyun Koo

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 such as the (1+1)~EA and Global SEMO can efficiently…

Neural and Evolutionary Computing · Computer Science 2022-06-07 Vahid Roostapour , Aneta Neumann , Frank Neumann

The phylogenetic tree construction is to infer the evolutionary relationship between species from the experimental data. However, the experimental data are often imperfect and conflicting each others. Therefore, it is important to extract…

Artificial Intelligence · Computer Science 2007-05-23 Andy Auyeung , Ajith Abraham

For a family of graphs $\mathcal{G}$, the $\mathcal{G}$-\textsc{Contraction} problem takes as an input a graph $G$ and an integer $k$, and the goal is to decide if there exists $F \subseteq E(G)$ of size at most $k$ such that $G/F$ belongs…

Discrete Mathematics · Computer Science 2020-08-19 Saket Saurabh , Uéverton dos Santos Souza , Prafullkumar Tale

In this paper we revisit the classical Edge Disjoint Paths (EDP) problem, where one is given an undirected graph G and a set of terminal pairs P and asks whether G contains a set of pairwise edge-disjoint paths connecting every terminal…

Data Structures and Algorithms · Computer Science 2017-11-07 Robert Ganian , Sebastian Ordyniak , M. S. Ramanujan