کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
509975 | 865730 | 2012 | 14 صفحه PDF | دانلود رایگان |
Frequency constraint structural optimization includes the exploration of highly nonlinear and non-convex search spaces with several local optima. These characteristics of the search spaces increase the possibility of the agents getting trapped in a local optimum, when using a meta-heuristic algorithm.In this paper a diversity index is introduced which together with a few other criteria, can be employed to recognize such traps. By the use of these concepts, a hybridization of the Charged System Search and the Big Bang-Big Crunch algorithms with trap recognition capability is proposed. Five numerical examples are considered to demonstrate the efficiency of the algorithm.
► Frequency constraint optimization is performed for highly nonlinear and non-convex search spaces.
► A hybridization of the CSS and BB-BC algorithms is proposed.
► A diversity index is introduced which is employed for trap recognition.
► Five numerical examples are presented to demonstrate the efficiency of the algorithm.
Journal: Computers & Structures - Volumes 102–103, July 2012, Pages 14–27