BVNS para el problema del bosque generador k-etiquetado
Sergio Consoli, Nenad Mladenov\`ic, Jos\`e A. Moreno-P\`erez

TL;DR
This paper introduces an efficient BVNS algorithm for the k-labeling forest problem, optimizing spanning forests with minimal components using limited labels, relevant for telecommunications and transport networks.
Contribution
It proposes a novel BVNS approach with strategies for setting neighborhood size, improving solutions for the k-labeling forest problem.
Findings
BVNS outperforms existing metaheuristics in solution quality
The strategy for setting neighborhood size significantly affects performance
Experimental results demonstrate the efficiency of the proposed method
Abstract
In this paper we propose an efficient solution for the problem of generating k-labeling forest VNS. This problem is an extension of the Minimum Spanning Tree Problem Labelling problem with important applications in telecommunications networks and multimodal transport. It is, given an undirected graph whose links are labeled, and an integer positive number k, find the spanning forest with the lowest number of connected components using at most k different labels. To address the problem a Basic Variable Neighbourhood Search is proposed where the maximum amplitude of the neighbourhood space, n, is a key parameter. Different strategies are studied to establish the value of n. BVNS with the best selected strategy is experimentally compared with other metaheuristics that have appeared in the literature applied to this type of problem.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVehicle Routing Optimization Methods · Data Management and Algorithms · Transportation Planning and Optimization
