An Efficient Pareto Set Identification Approach for Multiobjective Optimization on Black-Box Functions

Journal of Mechanical Design, Transactions Of the ASME - Tập 127 Số 5 - Trang 866-874 - 2005
Songqing Shan1, G. Gary Wang2,1
1Department of Mechanical and Manufacturing Engineering, University of Manitoba, Winnipeg, MB, R3T 5V6, Canada
2204-474-9463 204-275-7507

Tóm tắt

Both multiple objectives and computation-intensive black-box functions often exist simultaneously in engineering design problems. Few of existing multiobjective optimization approaches addresses problems with expensive black-box functions. In this paper, a new method called the Pareto set pursuing (PSP) method is developed. By developing sampling guidance functions based on approximation models, this approach progressively provides a designer with a rich and evenly distributed set of Pareto optimal points. This work describes PSP procedures in detail. From testing and design application, PSP demonstrates considerable promises in efficiency, accuracy, and robustness. Properties of PSP and differences between PSP and other approximation-based methods are also discussed. It is believed that PSP has a great potential to be a practical tool for multiobjective optimization problems.

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Thông tin xuất bản

Journal of Mechanical Design, Transactions Of the ASME

Tập 127 Số 5

866-874

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