دوره 16، شماره 1 - ( 11-1404 )
جلد 16 شماره 1 صفحات 47-31 |
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Shahrouzi M, Naserifar Y, Taghavi A M, Emamzadeh S. A HYBRID DIFFERENTIAL EVOLUTION AND SWARM ALGORITHM FOR ENGINEERING OPTIMIZATION. IJOCE 2026; 16 (1) :31-47
URL: http://ijoce.iust.ac.ir/article-1-661-fa.html
URL: http://ijoce.iust.ac.ir/article-1-661-fa.html
A HYBRID DIFFERENTIAL EVOLUTION AND SWARM ALGORITHM FOR ENGINEERING OPTIMIZATION. عنوان نشریه. 1404; 16 (1) :31-47
چکیده: (87 مشاهده)
Although metaheuristic algorithms are popular tools for global optimization, none of them is reported as the best for all problems. Hybridization is an advanced solution to overcome the shortcomings of individual methods by using the power points of the others. Here, a popular swarm intelligent algorithm with high explorative capability is combined with an exploitative operator of differential evolution and some dynamic parameter variation, as well as a greedy operator to enhance the search refinement. The proposed method is evaluated on a variety of engineering and constrained engineering problems, including the optimal design of Belleville Spring, pressure vessel, car side impact problem, and Morrow point dam. According to the results, considerable improvement is observed with respect to the standard particle swarm optimizer as well as competitive performance with a number of metaheuristic algorithms.
نوع مطالعه: پژوهشي |
موضوع مقاله:
Optimal design
دریافت: 1404/8/29 | پذیرش: 1404/10/18 | انتشار: 1404/10/27
دریافت: 1404/8/29 | پذیرش: 1404/10/18 | انتشار: 1404/10/27
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