Maximum linear arrangement: exact algorithms for specific classes of graphs and approximation algorithms for wide classes of graphs

Abstract Linear arrangements of graphs are a well-known type of graph labeling and are found in many important computational problems. A linear arrangement is usually defined as a permutation of the n vertices of a graph. An intuitive geometric setting is that of vertices lying on consecutive integer positions in the real line, starting at 1; edges are often drawn as semicircles above the real line. A well-known computational problem is the Minimum Linear Arrangement Problem () where the goal is to find an arrangement that minimizes the sum of edge lengths. In this paper we study the Maximum Linear Arrangement problem (), the counterpart of . We devise a new characterization of maximum arrangements of general graphs, and prove that can be solved for k -regular graphs ( $$k\le 2$$ k ≤ 2 ) in time $$O{\left( n\right) }$$ O n , and for k -linear trees ( $$k\le 2$$ k ≤ 2 ) in time $$O{\left( n\right) }$$ O n . We present two constrained variants of we call and . We prove that the former can be solved in time $$O{\left( n\right) }$$ O n for any connected bipartite graph; the latter can be solved by an algorithm that typically runs in time $$O{\left( n^3\log n\right) }$$ O n 3 log n on unlabeled trees. We show that is a 3/2-approximation algorithm for for trees.

Authors

Institutions

Publication Details

Journal
Journal of Combinatorial Optimization
Published
2026-08-20
DOI
https://doi.org/10.1007/s10878-026-01454-z
Primary Topic
Advanced Graph Theory Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Maximum linear arrangement: exact algorithms for specific classes of graphs and approximation algorithms for wide classes of graphs

Lluís Alemany-Puig, Ramon Ferrer‐i‐Cancho, Juan Luis Esteban
Journal of Combinatorial Optimization
Advanced Graph Theory Research
article

Maximum linear arrangement: exact algorithms for specific classes of graphs and approximation algorithms for wide classes of graphs

Lluís Alemany-Puig, Ramon Ferrer‐i‐Cancho, Juan Luis Esteban
article en

Abstract

Abstract Linear arrangements of graphs are a well-known type of graph labeling and are found in many important computational problems. A linear arrangement is usually defined as a permutation of the n vertices of a graph. An intuitive geometric setting is that of vertices lying on consecutive integer positions in the real line, starting at 1; edges are often drawn as semicircles above the real line. A well-known computational problem is the Minimum Linear Arrangement Problem () where the goal is to find an arrangement that minimizes the sum of edge lengths. In this paper we study the Maximum Linear Arrangement problem (), the counterpart of . We devise a new characterization of maximum arrangements of general graphs, and prove that can be solved for k -regular graphs ( $$k\le 2$$ k ≤ 2 ) in time $$O{\left( n\right) }$$ O n , and for k -linear trees ( $$k\le 2$$ k ≤ 2 ) in time $$O{\left( n\right) }$$ O n . We present two constrained variants of we call and . We prove that the former can be solved in time $$O{\left( n\right) }$$ O n for any connected bipartite graph; the latter can be solved by an algorithm that typically runs in time $$O{\left( n^3\log n\right) }$$ O n 3 log n on unlabeled trees. We show that is a 3/2-approximation algorithm for for trees.

Journal of Combinatorial OptimizationVol. 52(2)
Universitat Politècnica de Catalunya (ES)
Banco Santander, Ministerio de Ciencia, Innovación y Universidades, Generalitat de Catalunya, Ministerio de Ciencia e Innovación, Universitat Politècnica de Catalunya, Agencia Nacional de Investigación y Desarrollo, Agència de Gestió d'Ajuts Universitaris i de Recerca, Departament d'Universitats, Recerca i Societat de la Informació, Agencia Estatal de Investigación, European Social Fund
Openalex Percentile: Top 99%
Advanced Graph Theory Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.