چکیده مقاله
In the last two decades many researchers have implemented various kinds of meta heuristic algorithms in order to overcome the complex nature of the optimum design of structures Recently a new population based meta heuristic algorithm called the cuckoo search algorithm CS was developed which inspired by the behavior of some Cuckoo species in combination with the Lévy flight behavior of some birds and insects This paper describes the modifications made to the CS algorithm based on considering of memory strategy The improved version of CS entitled as Learned Cuckoo Search LCS In order to demonstrate the effectiveness and robustness of the learned version of CS, low weight design and performance comparisons are made between the original CS, LCS and other algorithms for some benchmark steel structures The results demonstratethat modifications improve the algorithm’s performance, especially in the aspect of computational effort
کلیدواژهها
نویسندگان
Taha Bakhshpoori
Faculty of Technology and Engineering, Department of Civil Engineering, East of Guilan, University of Guilan, Rudsar Vajargah, Iran
شیوه ارجاع
Bakhshpoori, Taha,1396,Optimum design of steel skeletal structures using learned cuckoo search algorithm,2rd International Conference on Soft Computing,Rudsar
ارائهشده در
مجموعه مقالات دومین کنفرانس ملی محاسبات نرم1 آذر 1396 · رودسر