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Wavelet multi-resolution approximation for multiobjective optimal control.

ABSTRACT: A new sequential method based on multi-resolution approximation is proposed for solving computationally expensive multi-objective optimization problems. A traditional strategy is to decompose a multi-objective optimization problem into a number of single-objective optimization problems, whereby the PF can be regarded as a function of weights. Therefore, it is very natural to use wavelet multi-resolution approximation techniques for setting weight vectors. In our framework, the sequential approach starts with sampling aggressive functions on the initial coarsest grid with a few collocation points; once a rough PF is obtained, new points are automatically added on the basis of an adaptive wavelet collocation method. Therefore, the PF can be approximated with a relatively small number of weights. The efficiency of our method is demonstrated on two examples: a typical multi-objective optimization problem and an expensive multi-objective control optimal problem.

SUBMITTER: Zou W

PROVIDER: S-EPMC6072063 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Wavelet multi-resolution approximation for multiobjective optimal control.

Zou Wen W Zhang Qingbin Q Gao Qingyu Q Feng Zhiwei Z

PloS one 20180802 8

A new sequential method based on multi-resolution approximation is proposed for solving computationally expensive multi-objective optimization problems. A traditional strategy is to decompose a multi-objective optimization problem into a number of single-objective optimization problems, whereby the PF can be regarded as a function of weights. Therefore, it is very natural to use wavelet multi-resolution approximation techniques for setting weight vectors. In our framework, the sequential approac ...[more]

PMID: 30071055

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