能量極小化的一種啟發(fā)式遺傳算法
A HEURISTIC GENETIC ALGORITHMS FOR ENERGY MINIMIZATION
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摘要: Chakradhar et.al(1988,1990)將組合電路表示為Hopfield神經(jīng)網(wǎng)絡(luò),將測(cè)試生成問(wèn)題轉(zhuǎn)化為一個(gè)組合優(yōu)化問(wèn)題。本文在傳統(tǒng)遺傳算法的基礎(chǔ)上,結(jié)合電路的拓?fù)湫畔?提出了一種用于組合電路神經(jīng)網(wǎng)絡(luò)模型能量極小化的啟發(fā)式遺傳算法。Abstract: Chakradhar, et al(1988, 1990) represent the combinational circuit as a Hopfield neural network and formulate the test generation problem as an optimization problem. In this paper, a heuristic genetic algorithms is proposed based on traditional GA and circuit topology information. The algorithm is used for energy minimization of combinaitonal circuit s neural networks.
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Chakradhar S T, Bushnell M L, Agrawal V D. Automatic test generation using neural netwarks. IEEE Int. Conf. on CAD, Santa chara: 1988, 416-419.[2]Chakradhar S T, Bushnell M L, Agrawal V D. Toward massively parallel automatic test generation. IEEE Trans. on CAD, 1990, CAD-9(9): 981-994.[3]Holland J H. Adaptation in natural and artifical system. Ann Arbor: The University of Michigan Press. 1975.[4]Goldberg D E. Genetic Algorithms in Search, Optimization and Machine Learning. Reading, Mass: Addison-Wesley, 1989, Chapter 5, 147-214. -
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