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A new hybrid prediction model with entropy-like kernel function for dynamic multi-objective optimization

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Abstract

Dynamic multi-objective problems (DMOPs) permeate all aspects of daily life and practical applications. As the variables of the search space or target space alter in pace with time, savants are also deepening the research on DMOPs, among which methods based on prediction mechanisms have been extensively developed. The historical optimal solutions can effectively predict the trend and location of the optimal solutions in the future. In this paper, a new hybrid prediction model (HPM) integrating the fuzzy linear prediction model with entropy-like kernel function and the one-step prediction model is developed to sort out DMOPs. In the method, the predicted center by the HPM prediction model is combined with the approximate manifold of PS to generate a trail population, and the linear one-step prediction model is utilized to generate another trail population. When the environment changes, the initial PS at the next moment is obtained by randomly crossing these two trail populations. To assess the proposed HPM model, it is compared with the reinitialization strategy, feedforward prediction strategy, population prediction strategy, T-S nonlinear regression strategy with multistep prediction and individual-based transfer learning under different MOEA optimizers for 22 benchmark problems. The results indicate that HPM has great advantages in solving these dynamic optimization problems.

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The data that support the findings of this study are available from the corresponding author upon request.

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Acknowledgements

This work is partially supported by the National Natural Science Foundation of China (No. 61976101), the University Natural Science Research Project of Anhui Province (No. KJ2019A0593) and the technical leaders and reserve candidates in Anhui Province under Grant No.2021H264.

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Authors and Affiliations

  1. School of Physics and Electronic Information, Huaibei Normal University, Huaibei, 235000, China

    Siyu Cao, Feng Zou, Hui Liu, Xuying Ji & Yan Zhang

  2. School of Computer Science and Technology, Huaibei Normal University, Huaibei, 235000, China

    Debao Chen

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  1. Siyu Cao
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  2. Feng Zou
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  3. Debao Chen
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  4. Hui Liu
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  5. Xuying Ji
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  6. Yan Zhang
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Correspondence to Feng Zou.

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Cao, S., Zou, F., Chen, D. et al. A new hybrid prediction model with entropy-like kernel function for dynamic multi-objective optimization. Appl Intell 53, 10500–10519 (2023). https://doi.org/10.1007/s10489-022-03934-1

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