arrow
Return

Efficient heuristics for the Steiner forest problem

delete2026-09-19
delete0
delete
OA
AI
M
Murilo Stockinger *
I
Isabel Rosseti
S
Simone de Lima Martins
L
Luidi Simonetti
A
Alexandre Plastino
DOI:10.1111/itor.70250delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Let be a connected undirected graph, a set of nodes, a set of edges, , and . Given a non-negative weight function associated with its edges, a set of terminal sets , the Steiner forest problem (SFP) consists of finding a subset of edges with the minimal cost such that all vertices of each (for ) lie in the same connected component in the graph induced by . In this work, as a first contribution, we propose a constructive algorithm for the SFP. Computational experiments on literature instances showed that the results obtained by the constructive algorithm outperformed the state-of-the-art primal-dual algorithm. Furthermore, as a second contribution, we present two heuristics to solve the SFP: the first, named GRASP-SFP, based on the GRASP metaheuristic, and the second, called MDM-GRASP-SFP, which incorporates a data mining component on GRASP-SFP. In most test instances provided in the literature, the results obtained by the two proposed algorithms tied for both best and average solution costs. Due to this fact, we generated more challenging SFP instances and the results reached by the proposed hybrid data mining heuristic improved upon those obtained by the original GRASP approach.
Keywords:
Steiner forest problem
GRASP
data mining
hybrid heuristics
metaheuristics
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

International Transactions in Operational Research cover
International Transactions in Operational Research
IF:
2.9
Papers:
1.8K
Citations:
3.7K

Organization

Universidade Federal Fluminense cover
Universidade Federal Fluminense
Scholars:
9.7K
Papers: 6.4K
Citations: 4.8K
U
Universidade Federal do Rio de Janeiro
Scholars:
2.9W
Papers: 1.8W
Citations: 1.6W
Cited Papers

Cited Papers

Distance Transformation for Network Design Problems
err2019-06-20
err0
errOAAI
errA. Ridha Mahjoub; Michael Poss; Luidi Simonetti; Eduardo Uchoa
errShare
errSave
errShare
errSave
Mining frequent patterns without candidate generation
err2000-05-16
err0
PREAI
errJiawei Han; Jian Pei; Yiwen Yin
errShare
errSave
errShare
errSave
errShare
errSave
Greedy Randomized Adaptive Search Procedures
err1995-03-01
err0
PREAI
errThomas A. Feo; Mauricio G. C. Resende
errShare
errSave
researcher View more