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A Weighted Coding in a Genetic Algorithm for the DegreeConstrained Minimum Spanning Tree Problem
, 2000
"... is a fundamental design choice in a genetic algorithm. This paper describes a novel coding of spanning trees in a genetic algorithm for the degreeconstrained minimum spanning tree problem. For a connected, weighted graph, this problem seeks to identify the shortest spanning tree whose degree does n ..."
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Cited by 20 (4 self)
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is a fundamental design choice in a genetic algorithm. This paper describes a novel coding of spanning trees in a genetic algorithm for the degreeconstrained minimum spanning tree problem. For a connected, weighted graph, this problem seeks to identify the shortest spanning tree whose degree does
An Efficient Evolutionary Algorithm for the DegreeConstrained Minimum Spanning Tree Problem
, 2000
"... The representation of candidate solutions and the variation operators are fundamental design choices in an evolutionary algorithm (EA). This paper proposes a novel representation technique and suitable variation operators for the degreeconstrained minimum spanning tree problem. For a weighted, undi ..."
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Cited by 26 (5 self)
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The representation of candidate solutions and the variation operators are fundamental design choices in an evolutionary algorithm (EA). This paper proposes a novel representation technique and suitable variation operators for the degreeconstrained minimum spanning tree problem. For a weighted
An AntBased Algorithm for Finding DegreeConstrained Minimum Spanning Tree
"... A spanning tree of a graph such that each vertex in the tree has degree at most d is called a degreeconstrained spanning tree. The problem of finding the degreeconstrained spanning tree of minimum cost in an edge weighted graph is well known to be NPhard. In this paper we give an AntBased algori ..."
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Cited by 6 (0 self)
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A spanning tree of a graph such that each vertex in the tree has degree at most d is called a degreeconstrained spanning tree. The problem of finding the degreeconstrained spanning tree of minimum cost in an edge weighted graph is well known to be NPhard. In this paper we give an Ant
Ant Colony Optimization Approaches to the Degreeconstrained Minimum Spanning Tree Problem
"... This paper presents the design of two Ant Colony Optimization (ACO) approaches and their improved variants on the degreeconstrained minimum spanning tree (dMST) problem. The first approach, which we call pACO, uses the vertices of the construction graph as solution components, and is motivated by ..."
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Cited by 2 (0 self)
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This paper presents the design of two Ant Colony Optimization (ACO) approaches and their improved variants on the degreeconstrained minimum spanning tree (dMST) problem. The first approach, which we call pACO, uses the vertices of the construction graph as solution components, and is motivated
DegreeConstrained Minimum Spanning Tree Problem Using Genetic Algorithm
"... Abstract—Computer network technology has been growing explosively and the multicast technology has become a hot Internet research topic. The main goal of multicast routing algorithm is seeking a minimum cost multicast tree in a given network, also known as the Steiner tree problem, which is a classi ..."
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Abstract—Computer network technology has been growing explosively and the multicast technology has become a hot Internet research topic. The main goal of multicast routing algorithm is seeking a minimum cost multicast tree in a given network, also known as the Steiner tree problem, which is a
A New Evolutionary Approach to the DegreeConstrained Minimum Spanning Tree Problem
 IEEE Transactions on Evolutionary Computation
, 1999
"... Finding the degreeconstrained minimum spanning tree (dMST) of a graph is a wellstudied NPhard problem of importance in communications network design and other networkrelated problems. In this paper we describe some previously proposed algorithms for solving the problem, and then introduce a nove ..."
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Cited by 10 (2 self)
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Finding the degreeconstrained minimum spanning tree (dMST) of a graph is a wellstudied NPhard problem of importance in communications network design and other networkrelated problems. In this paper we describe some previously proposed algorithms for solving the problem, and then introduce a
Variable Neighborhood Search For The DegreeConstrained Minimum Spanning Tree Problem
 Discrete Applied Mathematics
, 2001
"... . Given an undirected graph with weights associated with its edges, the degreeconstrained minimum spanning tree problem consists in finding a minimum spanning tree of the given graph, subject to constraints on node degrees. We propose a variable neighborhood search heuristic for the degreeconstrain ..."
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Cited by 16 (4 self)
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. Given an undirected graph with weights associated with its edges, the degreeconstrained minimum spanning tree problem consists in finding a minimum spanning tree of the given graph, subject to constraints on node degrees. We propose a variable neighborhood search heuristic for the degreeconstrained
Benchmark Problem Generators and Results for the Multiobjective DegreeConstrained Minimum Spanning Tree Problem
 In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO2001
, 1997
"... Finding a minimumweight spanning tree ..."
Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion and Generalization
, 1993
"... The paper describes a rankbased fitness assignment method for Multiple Objective Genetic Algorithms (MOGAs). Conventional niche formation methods are extended to this class of multimodal problems and theory for setting the niche size is presented. The fitness assignment method is then modified to a ..."
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Cited by 610 (15 self)
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The paper describes a rankbased fitness assignment method for Multiple Objective Genetic Algorithms (MOGAs). Conventional niche formation methods are extended to this class of multimodal problems and theory for setting the niche size is presented. The fitness assignment method is then modified
Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
 Evolutionary Computation
, 1994
"... In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands the user to have knowledge about t ..."
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Cited by 524 (4 self)
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the underlying problem. Moreover, in solving multiobjective problems, designers may be interested in a set of Paretooptimal points, instead of a single point. Since genetic algorithms(GAs) work with a population of points, it seems natural to use GAs in multiobjective optimization problems to capture a
Results 1  10
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363,406