Neighbourhood searches for the bounded diameter minimum spanning tree problem embedded in a VNS, EA, and ACO

Authors:
Martin Gruber;Jano van Hemert;Günther R. Raidl
Affiliations:
Vienna University of Technology, Vienna, Austria;University of Edinburgh, Edinburgh, UK;Vienna University of Technology, Vienna, Austria
Venue:
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Year:
2006

Citing 8
Cited 13

A tree-based algorithm for distributed mutual exclusion

ACM Transactions on Computer Systems (TOCS)
Compression of correlated bit-vectors

Information Systems
Computers and Intractability: A Guide to the Theory of NP-Completeness

Computers and Intractability: A Guide to the Theory of NP-Completeness
Greedy heuristics and an evolutionary algorithm for the bounded-diameter minimum spanning tree problem

Proceedings of the 2003 ACM symposium on Applied computing
Experimental Analysis of Practically Efficient Algorithms for Bounded-Hop Accumulation in Ad-Hoc Wireless Networks

IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 12 - Volume 13
A 2-path approach for odd-diameter-constrained minimum spanning and Steiner trees

Networks
Greedy heuristics for the bounded diameter minimum spanning tree problem

Journal of Experimental Algorithmics (JEA)
Ant colony system: a cooperative learning approach to the traveling salesman problem

IEEE Transactions on Evolutionary Computation

On quality performance of heuristic and evolutionary algorithms for biobjective minimum spanning trees

Proceedings of the 9th annual conference on Genetic and evolutionary computation
Ant colony-based algorithm for constructing broadcasting tree with degree and delay constraints

Expert Systems with Applications: An International Journal
The node-depth encoding: analysis and application to the bounded-diameter minimum spanning tree problem

Proceedings of the 10th annual conference on Genetic and evolutionary computation
Greedy heuristics for the bounded diameter minimum spanning tree problem

Journal of Experimental Algorithmics (JEA)
LS(graph & tree): a local search framework for constraint optimization on graphs and trees

Proceedings of the 2009 ACM symposium on Applied Computing
Exploiting hierarchical clustering for finding bounded diameter minimum spanning trees on euclidean instances

Proceedings of the 11th Annual conference on Genetic and evolutionary computation
New heuristic and hybrid genetic algorithm for solving the bounded diameter minimum spanning tree problem

Proceedings of the 11th Annual conference on Genetic and evolutionary computation
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
Restricted dynamic programming based neighborhoods for the hop-constrained minimum spanning tree problem

Journal of Heuristics
A learning automata-based heuristic algorithm for solving the minimum spanning tree problem in stochastic graphs

The Journal of Supercomputing
A memetic algorithm and a solution archive for the rooted delay-constrained minimum spanning tree problem

EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
LS(Graph): a constraint-based local search for constraint optimization on trees and paths

Constraints
Degree constrained minimum spanning tree problem: a learning automata approach

The Journal of Supercomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We consider the Bounded Diameter Minimum Spanning Tree problem and describe four neighbourhood searches for it. They are used as local improvement strategies within a variable neighbourhood search (VNS), an evolutionary algorithm (EA) utilising a new encoding of solutions, and an ant colony optimisation (ACO). We compare the performance in terms of effectiveness between these three hybrid methods on a suite of popular benchmark instances, which contains instances too large to solve by current exact methods. Our results show that the EA and the ACO outperform the VNS on almost all used benchmark instances. Furthermore, the ACO yields most of the time better solutions than the EA in long-term runs, whereas the EA dominates when the computation time is strongly restricted.