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Neighbor-Interactive Bee Colony for Problems with Local Structures

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Abstract
In this letter, we integrate domain information into the original artificial bee colony algorithm to create a novel, neighbor interactive bee colony algorithm. We use the Hamming distance measure to compute variable dependency between two binary variables and employ the Gini correlation coefficient to compute variable relation between integer variables. The proposed optimization method was evaluated by minimizing binary Ising models, integer Potts models, and trapped functions. Experimental results show that the proposed method outperformed the traditional artificial bee colony and other meta-heuristics in all the testing cases.
Author(s)
Phuc Nguyen HongAhn, Chang WookJeong, Jaehoon (Paul)
Issued Date
2017-09
Type
Article
DOI
10.1587/transfun.E100.A.2034
URI
https://scholar.gist.ac.kr/handle/local/13599
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Citation
Ieice Transactions on Fundamentals of Electronics Communications and Computer Sciences, v.E100A, no.9, pp.2034 - 2037
ISSN
1745-1337
Appears in Collections:
Department of AI Convergence > 1. Journal Articles
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