Target matching problems and an adaptive constraint strategy for multiobjective design optimization using genetic algorithms

Authors:
N. F. Wang;K. Tai
Affiliations:
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, Guangdong 510640, People's Republic of China;School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Ave, Singapore 639798, Singapore
Venue:
Computers and Structures
Year:
2010

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Abstract

In multiobjective design optimization problems, the designer may know that some objectives are harder to extremize than others or that some regions of the objective space are more desirable/important. Such useful information can be incorporated into the genetic algorithm optimization procedure by treating the more challenging/important objectives as constraints whose ideal values are adaptively improved/tightened during the procedure to guide the search. Employing this adaptive constraint strategy and a morphological representation of geometric variables, a genetic algorithm was developed and evaluated through special 'Target Matching' test problems which are simulated topology/shape optimization problems with multiple objectives and constraints.