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Performance of a genetic algorithm for the graph partitioning problem

✍ Scribed by Keiko Kohmoto; Kengo Katayama; Hiroyuki Narihisa

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
653 KB
Volume
38
Category
Article
ISSN
0895-7177

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✦ Synopsis

MATHEMATICAL l OWl"lD ." *ClaNCC d COMPUTER DIRmCT* MODELLING Mathematical and Computer Modelling 38 (2003)

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Many heuristics such as iterative improvement and simulated annealing are available in the literature which try to give a near-optimal solution to the graph partitioning problem. Recently, a new method called the noising method has been proposed for solving combinatorial optimization problems. The n

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## Abstract In this paper, the author explains the recent evolution of algorithms for minimum partitioning problems in graphs. When the set of vertices of a graph having non‐negative weights for edges is divided into __k__ subsets, the set of edges for which both endpoints are contained in differen