Presentation information

General Session

General Session » GS-2 Machine learning

[4G3-GS-2l] 機械学習:学習方略(1/2)

Fri. Jun 11, 2021 1:40 PM - 3:20 PM Room G (GS room 2)

座長:内部 英治(ATR)

2:40 PM - 3:00 PM

[4G3-GS-2l-04] Genetic Algorithm using Bayesian Optimization Algorithm for Combinatorial Optimization

〇Tomoyuki Hiranuma1, Shoya Yasuda1, Kense Todo1, Maho Taniguchi1, Masayuki Yamamura1 (1. Tokyo Institute of Technology)

Keywords:Genetic Algorithm, Evolutionary Computation, Combinatorial Optimization, Bayesian Optimization Algorithm

In genetic algorithm(GA), it is considered important to preserve the distribution of the population by designing a crossover which inherits the good parental feature and generation alternation model which maintains the diversity of population. However, there are no general GAs which used in combinatorial optimization problems, even though it can be used in functional optimization problems by preserving statistics. In this study, we propose a new framework of GA using bayesian networks inspired by Bayesian Optimization Algorithm(BOA). The results show that the proposed method can be expected to be a general algorithm in combinatorial optimization problems.

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