Simulated annealing - an annotated bibliography
American Journal of Mathematical and Management Sciences
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
A tabu search heuristic for the vehicle routing problem
Management Science
Approximate solution of NP optimization problems
Theoretical Computer Science
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Low-Degree Spanning Trees of Small Weight
SIAM Journal on Computing
Data structures for on-line updating of minimum spanning trees
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Polynomial time approximation schemes for Euclidean TSP and other geometric problems
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Variable neighborhood search for the degree-constrained minimum spanning tree problem
Discrete Applied Mathematics - Special issue: Third ALIO-EURO meeting on applied combinatorial optimization
Redundant representations in evolutionary computation
Evolutionary Computation
Using Lagrangian dual information to generate degree constrained spanning trees
Discrete Applied Mathematics - Special issue: IV ALIO/EURO workshop on applied combinatorial optimization
An ant-based algorithm for finding degree-constrained minimum spanning tree
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Multi-objective optimization scheme for multicast flows: a survey, a model and a MOEA solution
LANC '05 Proceedings of the 3rd international IFIP/ACM Latin American conference on Networking
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
LS(graph & tree): a local search framework for constraint optimization on graphs and trees
Proceedings of the 2009 ACM symposium on Applied Computing
VNS and second order heuristics for the min-degree constrained minimum spanning tree problem
Computers and Operations Research
Computers and Operations Research
End System Multicast routing for multi-party videoconferencing applications
Computer Communications
On the bias and performance of the edge-set encoding
IEEE Transactions on Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Using Lagrangian dual information to generate degree constrained spanning trees
Discrete Applied Mathematics - Special issue: IV ALIO/EURO workshop on applied combinatorial optimization
The property analysis of evolutionary algorithms applied to spanning tree problems
Applied Intelligence
A primal branch-and-cut algorithm for the degree-constrained minimum spanning tree problem
WEA'07 Proceedings of the 6th international conference on Experimental algorithms
The Journal of Supercomputing
An ant colony optimization approach to the degree-constrained minimum spanning tree problem
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Degree constrained minimum spanning tree problem: a learning automata approach
The Journal of Supercomputing
Towards optimal neuronal wiring through estimation of distribution algorithms
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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The Degree Constrained Minimum Spanning Tree (DCMST) on a graph is the problem of generating a minimum spanning tree with constraints on the number of arcs that can be incident to vertices of the graph. In this paper we develop three heuristics for the DCMST, including simulated annealing, a genetic algorithm and a method based on problem space search. We propose alternative tree representations to facilitate the neighbourhood searches for the genetic algorithm. The tree representation that we use for the genetic algorithm can be generalised to other tree optimisation problems as well. We compare the computational performance of all of these approaches against the performance of an exact solution approach in the literature. In addition, we also develop a new exact solution approach based on the combinatorial structure of the problem. We test all of these approaches using standard problems taken from the literature and some new test problems that we generate.