A multilevel heuristic for the rooted delay-constrained minimum spanning tree problem

Authors:
Martin Berlakovich;Mario Ruthmair;Günther R. Raidl
Affiliations:
Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria;Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria;Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria
Venue:
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Year:
2011

Citing 6
Cited 0

Modeling and solving the rooted distance-constrained minimum spanning tree problem

Computers and Operations Research
A Path Relinking Approach for Delay-Constrained Least-Cost Multicast Routing Problem

ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
A Kruskal-Based Heuristic for the Rooted Delay-Constrained Minimum Spanning Tree Problem

Computer Aided Systems Theory - EUROCAST 2009
Variable neighborhood search and ant colony optimization for the rooted delay-constrained minimum spanning tree problem

PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
A layered graph model and an adaptive layers framework to solve delay-constrained minimum tree problems

IPCO'11 Proceedings of the 15th international conference on Integer programming and combinatoral optimization
A hybrid scatter search meta-heuristic for delay-constrained multicast routing problems

Applied Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

The rooted delay-constrained minimum spanning tree problem is an NP-hard combinatorial optimization problem. The problem appears in practice for example when designing a distribution network with a guarantee of timely delivery. Another example is be a centralized broadcasting network where the delaybound represents a quality of service constraint. We introduce a multilevel-based construction heuristic which uses a new measurement for the suitability of edges to create a solution for the problem. In comparison to existing heuristics the main intention is not to create a minimum cost spanning tree, but a solution with a high potential for further improvement. Experimental results indicate that in most cases our approach produces solutions that after local improvement are of higher quality than those of other existing construction techniques.