Optimal Design of Truss Structures with Discrete Variables Using Colliding Bodies Optimization

2015 ◽  
pp. 87-104 ◽  
Author(s):  
A. Kaveh ◽  
V. R. Mahdavi
Structures ◽  
2021 ◽  
Vol 29 ◽  
pp. 843-862
Author(s):  
Farqad K.J. Jawad ◽  
Mohammed Mahmood ◽  
Dansheng Wang ◽  
Osama AL-Azzawi ◽  
Anas AL-JAMELY

2015 ◽  
Vol 12 (9) ◽  
pp. 1721-1747 ◽  
Author(s):  
Shahin Jalili ◽  
Yousef Hosseinzadeh

2016 ◽  
Vol 38 (4) ◽  
pp. 307-317
Author(s):  
Pham Hoang Anh

In this paper, the optimal sizing of truss structures is solved using a novel evolutionary-based optimization algorithm. The efficiency of the proposed method lies in the combination of global search and local search, in which the global move is applied for a set of random solutions whereas the local move is performed on the other solutions in the search population. Three truss sizing benchmark problems with discrete variables are used to examine the performance of the proposed algorithm. Objective functions of the optimization problems are minimum weights of the whole truss structures and constraints are stress in members and displacement at nodes. Here, the constraints and objective function are treated separately so that both function and constraint evaluations can be saved. The results show that the new algorithm can find optimal solution effectively and it is competitive with some recent metaheuristic algorithms in terms of number of structural analyses required.


Author(s):  
Leonard P. Pomrehn ◽  
Panos Y. Papalambros

Abstract The use of discrete variables in optimal design models offers the opportunity to deal rigorously with an expanded variety of design situations, as opposed to using only continuous variables. However, complexity and solution difficulty increase dramatically and model formulation becomes very important. A particular problem arising from the design of a gear train employing four spur gear pairs is introduced and formulated in several different ways. An interesting aspect of the problem is its exhibition of three different types of discreteness. The problem could serve as a test for a variety of optimization or artificial intellegence techniques. The best known solution is included in this article, while its derivation is given in a sequel article.


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