Multi-objective problems are encountered in many engineering applications and multi-objective optimization (MOO) approaches have been proposed to search for Pareto solutions. Due to the nature of searching for multiple optimal solutions, the computational efforts of MOO can be a serious concern. To improve the computational efficiency, a novel efficient sequential MOO (S-MOO) approach is proposed in this work, in which anchor points in the design space for global variables are fully utilized and a data set for global solutions is generated to guide the search for Pareto solutions. Global variables refer to those shared by more than one objective or constraint, while local variables appear only in one objective and corresponding constraints. As a matter of fact, it is the existence of global variables that leads to couplings among the multiple objectives. The proposed S-MOO breaks the couplings among multiple objectives (and constraints) by distinguishing the global variables, and thus all objectives are optimized in a sequential manner within each iteration while all iterations can be processed in parallel. The computational cost per produced Pareto point is reduced and a well-spread Pareto front is obtained. Six numerical and engineering examples including two three-objective problems are tested to demonstrate the applicability and efficiency of the proposed approach.
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December 2016
Research-Article
A Novel Sequential Multi-Objective Optimization Using Anchor Points in the Design Space of Global Variables
Jianhua Zhou,
Jianhua Zhou
National Engineering Laboratory for the
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Search for other works by this author on:
Mian Li,
Mian Li
National Engineering Laboratory for the
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China;
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China;
University of Michigan-Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: mianli@sjtu.edu.cn
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: mianli@sjtu.edu.cn
Search for other works by this author on:
Min Xu
Min Xu
National Engineering Laboratory for the
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Search for other works by this author on:
Jianhua Zhou
National Engineering Laboratory for the
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Mian Li
National Engineering Laboratory for the
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China;
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China;
University of Michigan-Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: mianli@sjtu.edu.cn
University Joint Institute,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: mianli@sjtu.edu.cn
Min Xu
National Engineering Laboratory for the
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
Automotive Electronic Control Technology,
Shanghai Jiao Tong University,
Shanghai 200240, China
1Corresponding author.
Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received February 1, 2016; final manuscript received August 24, 2016; published online October 3, 2016. Assoc. Editor: Harrison M. Kim.
J. Mech. Des. Dec 2016, 138(12): 121406 (11 pages)
Published Online: October 3, 2016
Article history
Received:
February 1, 2016
Revised:
August 24, 2016
Citation
Zhou, J., Li, M., and Xu, M. (October 3, 2016). "A Novel Sequential Multi-Objective Optimization Using Anchor Points in the Design Space of Global Variables." ASME. J. Mech. Des. December 2016; 138(12): 121406. https://doi.org/10.1115/1.4034671
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