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JACIII Vol.22 No.2 pp. 236-241
doi: 10.20965/jaciii.2018.p0236
(2018)

Paper:

Solving Order/Degree Problems by Using EDA-GK with a Novel Sampling Method

Ryoichi Hasegawa and Hisashi Handa

Kindai University
3-4-1 Kowakae, Higashi-Osaka 577-8502, Japan

Received:
August 20, 2017
Accepted:
January 11, 2018
Published:
March 20, 2018
Keywords:
Estimation of Distribution Algorithms, graph kernel, Order/Degree problems
Abstract

The Estimation of Distribution Algorithms with Graph Kernels called EDA-GK is an extension of the Estimation of Distribution Algorithms that can work with graph-related problems. Individuals of the EDA-GK are represented by graphs. In this paper, the EDA-GK is applied to solve for the Order/Degree problems, which are an NP-hard problems and are a benchmark problem in graph theory studies. Moreover, we incorporate a new sampling method for generating offspring. Experimental results on several problem instances of Order/Degree problems show the effectiveness of the EDA-GK.

Cite this article as:
R. Hasegawa and H. Handa, “Solving Order/Degree Problems by Using EDA-GK with a Novel Sampling Method,” J. Adv. Comput. Intell. Intell. Inform., Vol.22, No.2, pp. 236-241, 2018.
Data files:
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Last updated on Aug. 17, 2018