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This paper analyses a $(1,\lambda)$-Evolution Strategy, a randomised comparison-based adaptive search algorithm, on a simple constraint optimisation problem. The algorithm uses resampling to handle the constraint and optimizes a linear…

Neural and Evolutionary Computing · Computer Science 2014-12-09 Alexandre Chotard , Anne Auger , Nikolaus Hansen

Given a set of points in the Euclidean plane, the Euclidean \textit{$\delta$-minimum spanning tree} ($\delta$-MST) problem is the problem of finding a spanning tree with maximum degree no more than $\delta$ for the set of points such the…

Combinatorics · Mathematics 2018-09-26 Patrick J. Andersen , Charl J. Ras

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

An elastic-degenerate string is a sequence of $n$ finite sets of strings of total length $N$, introduced to represent a set of related DNA sequences, also known as a pangenome. The ED string matching (EDSM) problem consists in reporting all…

Data Structures and Algorithms · Computer Science 2022-09-05 Giulia Bernardini , Estéban Gabory , Solon P. Pissis , Leen Stougie , Michelle Sweering , Wiktor Zuba

We study the minimum \emph{Monitoring Edge Geodetic Set} (\megset) problem introduced in [Foucaud et al., CALDAM'23]: given a graph $G$, we say that an edge is monitored by a pair $u,v$ of vertices if \emph{all} shortest paths between $u$…

Data Structures and Algorithms · Computer Science 2025-10-09 Davide Bilò , Giordano Colli , Luca Forlizzi , Stefano Leucci

Pseudo-Boolean monotone functions are unimodal functions which are trivial to optimize for some hillclimbers, but are challenging for a surprising number of evolutionary algorithms (EAs). A general trend is that EAs are efficient if…

Neural and Evolutionary Computing · Computer Science 2021-04-09 Johannes Lengler , Xun Zou

In recent years, many design automation methods have been developed to routinely create approximate implementations of circuits and programs that show excellent trade-offs between the quality of output and required resources. This paper…

Neural and Evolutionary Computing · Computer Science 2021-08-17 Lukas Sekanina

Recent LLM-guided evolutionary search methods have shown that iterative program mutation can discover strong algorithms, but they typically optimize each task independently, even when related tasks share reusable structure. We introduce…

Machine Learning · Computer Science 2026-05-22 Halil Alperen Gozeten , Xuechen Zhang , Emrullah Ildiz , Ege Onur Taga , Tara Javidi , Samet Oymak

In the length-constrained minimum spanning tree (MST) problem, we are given an $n$-node edge-weighted graph $G$ and a length constraint $h \geq 1$. Our goal is to find a spanning tree of $G$ whose diameter is at most $h$ with minimum…

Data Structures and Algorithms · Computer Science 2025-06-17 D Ellis Hershkowitz , Richard Z Huang

The focus of this paper is two fold. Firstly, we present a logical approach to graph modification problems such as minimum node deletion, edge deletion, edge augmentation problems by expressing them as an expression in first order (FO)…

Logic in Computer Science · Computer Science 2017-11-09 Kona Harshita , Sounaka Mishra , Renjith. P , N. Sadagopan

We introduce a new benchmark problem called Deceptive Leading Blocks (DLB) to rigorously study the runtime of the Univariate Marginal Distribution Algorithm (UMDA) in the presence of epistasis and deception. We show that simple Evolutionary…

Neural and Evolutionary Computing · Computer Science 2019-07-30 Per Kristian Lehre , Phan Trung Hai Nguyen

In this paper we solve the ancestry-labeling scheme problem which aims at assigning the shortest possible labels (bit strings) to nodes of rooted trees, so that ancestry queries between any two nodes can be answered by inspecting their…

Data Structures and Algorithms · Computer Science 2016-11-23 Pierre Fraigniaud , Amos Korman

Addressing a complex real-world optimization problem is a challenging task. The chance-constrained knapsack problem with correlated uniform weights plays an important role in the case where dependent stochastic components are considered. We…

Data Structures and Algorithms · Computer Science 2021-02-12 Yue Xie , Aneta Neumann , Frank Neumann , Andrew M. Sutton

The Minimum Linear Arrangement problem (MLA) consists of finding a mapping $\pi$ from vertices of a graph to distinct integers that minimizes $\sum_{\{u,v\}\in E}|\pi(u) - \pi(v)|$. In that setting, vertices are often assumed to lie on a…

Data Structures and Algorithms · Computer Science 2025-11-05 Lluís Alemany-Puig , Juan Luis Esteban , Ramon Ferrer-i-Cancho

The performance of base-line Evolutionary Algorithms (EAs) on combinatorial problems has been studied rigorously. From the theoretical viewpoint, the literature extensively investigates the linear problems, while the theoretical analysis of…

Neural and Evolutionary Computing · Computer Science 2019-07-02 Vahid Roostapour , Mojgan Pourhassan , Frank Neumann

Recent works showed that simple success-based rules for self-adjusting parameters in evolutionary algorithms (EAs) can match or outperform the best fixed parameters on discrete problems. Non-elitism in a (1,$\lambda$) EA combined with a…

Neural and Evolutionary Computing · Computer Science 2022-04-13 Mario Alejandro Hevia Fajardo , Dirk Sudholt

For a metric graph $G=(V,E)$ and $R\subset V$, the internal Steiner minimum tree problem asks for a minimum weight Steiner tree spanning $R$ such that every vertex in $R$ is not a leaf. This note shows a simple polynomial-time…

Data Structures and Algorithms · Computer Science 2013-07-18 Bang Ye Wu

The study of genetic map linearization leads to a combinatorial hard problem, called the {\em minimum breakpoint linearization} (MBL) problem. It is aimed at finding a linearization of a partial order which attains the minimum breakpoint…

Genomics · Quantitative Biology 2015-02-26 Xin Chen

Experience shows that typical evolutionary algorithms can cope well with stochastic disturbances such as noisy function evaluations. In this first mathematical runtime analysis of the $(1+\lambda)$ and $(1,\lambda)$ evolutionary algorithms…

Neural and Evolutionary Computing · Computer Science 2024-07-17 Denis Antipov , Benjamin Doerr , Alexandra Ivanova

When globally optimal solutions of complicated optimization problems cannot be located by evolutionary algorithms (EAs) in polynomial expected running time, the hitting time/running time analysis is not flexible enough to accommodate the…

Neural and Evolutionary Computing · Computer Science 2020-12-01 Cong Wang , Yu Chen , Jun He , Chengwang Xie