کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
511644 | 865885 | 2010 | 13 صفحه PDF | دانلود رایگان |
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.
Journal: Computers & Structures - Volume 88, Issues 19–20, October 2010, Pages 1064–1076