A Q-learning based multi-objective function optimization strategy

SONG TianHeng1;LI DaZi1;GAO YanChen2

Journal of Beijing University of Chemical Technology ›› 2011, Vol. 38 ›› Issue (5) : 125-129.

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Journal of Beijing University of Chemical Technology ›› 2011, Vol. 38 ›› Issue (5) : 125-129.
机电工程和信息科学

A Q-learning based multi-objective function optimization strategy

  • SONG TianHeng1;LI DaZi1;GAO YanChen2
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Abstract

In this paper, a multi-optimization strategy is proposed based on combining the Q-learning algorithm and Pareto sorting. Multiple objective functions of the problem are described with the help of a Q-learning rewards strategy. Combined with Pareto sorting, the proposed strategy generates a non-dominated solution set close enough to a real Pareto front after limited iterations. Compared with other intelligent algorithms, it offers the advantages of a simpler structure, learning without prior knowledge, and fewer parameters. The results with test functions prove the validity of the proposed strategy. This method therefore provides an alternative means of intelligent optimization in this area.

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SONG TianHeng1;LI DaZi1;GAO YanChen2. A Q-learning based multi-objective function optimization strategy[J]. Journal of Beijing University of Chemical Technology, 2011, 38(5): 125-129

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