Adaptive multi-objective optimization based on feedback design |
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| Authors: | DOU Liqian ZONG Qun JI Yuehui ZENG Fanlin |
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| Institution: | DOU Liqian,ZONG Qun,JI Yuehui,ZENG Fanlin(School of Electrical Engineering and Automation,Tianjin University,Tianjin 300072,China) |
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| Abstract: | The problem of adaptive multi-objective optimization (AMOO) has received extensive attention due to its practical significance.
An important issue in optimizing a multi-objective system is adjusting the weighting coefficients of multiple objectives so
as to keep track of various conditions. In this paper, a feedback structure for AMOO is designed. Moreover, the reinforcement
learning combined with hidden biasing information is applied to online tuning weighting coefficients of objective functions.
Finally, the proposed approach is applied to the optimization design problem of an elevator group control system. Simulation
results show that AMOO has the best average performance at up-peak traffic profile, and its average waiting time reaches 22
s. AMOO is suitable for various traffic patterns, and it is also superior to the majority of algorithms at down-peak traffic
profile. |
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| Keywords: | multi-objective optimization adaptive optimization reinforcement learning elevator group system |
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