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Combination of Evolutionary Algorithms with Experimental Design and Traditional Optimization

發(fā)布時(shí)間:2016-10-29 瀏覽:

講座題目:Combination of Evolutionary Algorithms with Experimental Design and Traditional Optimization

講座人:張青富 教授

講座時(shí)間:15:00

講座日期:2016-10-29

地點(diǎn):長(zhǎng)安校區(qū) 文津樓三段522研討室

主辦單位:計(jì)算機(jī)科學(xué)學(xué)院 生物大數(shù)據(jù)計(jì)算科研團(tuán)隊(duì)

講座內(nèi)容:Evolutionary algorithmsalone cannot solve optimization problems very efficiently since there are many random (not very rational) decisions in these algorithms. Combination of evolutionary algorithms and other techniques have been proven to be an efficient optimization methodology. In this talk, I will explain the basic ideas of our three algorithms along this line (1): Orthogonal genetic algorithm which treats crossover/mutation as an experimental design problem, and (2)Multi objective evolutionary algorithm based on decomposition (MOEA/D) which uses decomposition techniques from traditional mathematical programming in multi objective optimization evolutionary algorithm.

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