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Solving Large-Scale TSP Using Adaptive Clustering Method
- Source :
- ISCID (1)
- Publication Year :
- 2009
- Publisher :
- IEEE, 2009.
-
Abstract
- TSP is a well-known NP-hard problem. Although many algorithms for solving TSP, such as linear programming, dynamic programming, genetic algorithm, anneal algorithm, and ACO algorithm have been proven to be effective, they are not so suitable for the more complicated large scale TSP. This paper offers a method to decompose the large-scale data into several small-scale data sets by its relativity; and the results of each small-scale data set which represents a small-scale TSP compose the whole result of the large-scale TSP. An adaptive clustering method is presented and a novel genetic algorithm for TSP is described in this paper.
- Subjects :
- Mathematical optimization
Computational complexity theory
Linear programming
Scale (ratio)
Computer science
Computer Science::Neural and Evolutionary Computation
MathematicsofComputing_NUMERICALANALYSIS
Computer Science::Computational Complexity
Travelling salesman problem
Data set
Dynamic programming
TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY
Genetic algorithm
Computer Science::Data Structures and Algorithms
Cluster analysis
Algorithm
MathematicsofComputing_DISCRETEMATHEMATICS
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2009 Second International Symposium on Computational Intelligence and Design
- Accession number :
- edsair.doi...........6c4ece55e9537ea5c8e74b843e5a87b5