دوره 8، شماره 1 - ( 10-1396 )                   جلد 8 شماره 1 صفحات 75-53 | برگشت به فهرست نسخه ها

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Shahrouzi M, Farah-Abadi H. A FAST FUZZY-TUNED MULTI-OBJECTIVE OPTIMIZATION FOR SIZING PROBLEMS. IJOCE 2018; 8 (1) :53-75
URL: http://ijoce.iust.ac.ir/article-1-325-fa.html
A FAST FUZZY-TUNED MULTI-OBJECTIVE OPTIMIZATION FOR SIZING PROBLEMS. عنوان نشریه. 1396; 8 (1) :53-75

URL: http://ijoce.iust.ac.ir/article-1-325-fa.html


چکیده:   (20064 مشاهده)

The most recent approaches of multi-objective optimization constitute application of meta-heuristic algorithms for which, parameter tuning is still a challenge. The present work hybridizes swarm intelligence with fuzzy operators to extend crisp values of the main control parameters into especial fuzzy sets that are constructed based on a number of prescribed facts. Such parameter-less particle swarm optimization is employed as the core of a multi-objective optimization framework with a repository to save Pareto solutions. The proposed method is tested on a variety of benchmark functions and structural sizing examples. Results show that it can provide Pareto front by lower computational time in competition with some other popular multi-objective algorithms.

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نوع مطالعه: پژوهشي | موضوع مقاله: Optimal design
دریافت: 1396/4/10 | پذیرش: 1396/4/10 | انتشار: 1396/4/10

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