دوره 9، شماره 3 - ( 3-1398 )                   جلد 9 شماره 3 صفحات 411-422 | برگشت به فهرست نسخه ها

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Sedaghat Shayegan D, Lork A, Hashemi S. MOUTH BROODING FISH ALGORITHM FOR COST OPTIMIZATION OF REINFORCED CONCRETE ONE-WAY RIBBED SLABS. International Journal of Optimization in Civil Engineering. 2019; 9 (3) :411-422
URL: http://ijoce.iust.ac.ir/article-1-398-fa.html
MOUTH BROODING FISH ALGORITHM FOR COST OPTIMIZATION OF REINFORCED CONCRETE ONE-WAY RIBBED SLABS. دانشگاه علم و صنعت ایران. 1398; 9 (3) :411-422

URL: http://ijoce.iust.ac.ir/article-1-398-fa.html


چکیده:   (192 مشاهده)
In this paper, the optimum design of a reinforced concrete one-way ribbed slab, is presented via recently developed metaheuristic algorithm, namely, the Mouth Brooding Fish (MBF). Meta-heuristics based on evolutionary computation and swarm intelligence are outstanding examples of nature-inspired solution techniques. The MBF algorithm simulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. This algorithm uses the movement, dispersion and protection behavior of Mouth Brooding Fish as a pattern to find the best possible answer. The cost of the system is considered to be the objective function, and the design is based on the American Concrete Institute’s ACI 318-08 standard. The performance of this algorithm is compared with harmony search (HS), colliding bodies optimization (CBO), particle swarm optimization (PSO), democratic particle swarm optimization (DPSO), charged system search (CSS) and enhanced charged system search (ECSS). The numerical results demonstrate that the MBF algorithm is able to construct very promising results and has merits in solving challenging optimization problems.
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نوع مطالعه: پژوهشي | موضوع مقاله: Applications
دریافت: ۱۳۹۷/۱۱/۲۹ | پذیرش: ۱۳۹۷/۱۱/۲۹ | انتشار: ۱۳۹۷/۱۱/۲۹

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