Optimum design of steel structures via artificial bee colony (abc) algorithm and SAP2000

Eser, Cengiz
Over the past few years, metaheuristic optimization techniques have received considerable attention from engineering researchers. Under metaheuristics, swarm intelligence based algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design constraints imposed by design codes. In this study, artificial bee colony algorithm (ABC) is utilized to optimize four truss structures from real life and literature. ABC algorithm is one of those popular techniques which has proved to be effective when solving combinatorial and nonlinear optimization problems such as scheduling, routing, financial product design and other problem areas. In this thesis, the results of the ABC algorithm are compared with the results of other optimization algorithms from the literature to investigate the use and efficiency of this technique for solving steel truss design problems. Artificial bee colony algorithm is computerized in VB.NET platform to develop software called ABC-SOP2014. ABC-SOP2014 is capable to interact with well-known structural analysis and design software SAP2000 through the Open Application Programming Interface (OAPI) for size optimum design of steel structures. In this study the program is used only for discrete size optimization of steel truss structures with penalty function implementation aiming minimum weight according to design limitations imposed by AISC-ASD (Allowable Stress Design Code of American Institute of Steel Construction) or limitations specified for the problem without any code requirement. The results reveal that the ABC algorithm can be used effectively as an optimization technique for truss structures, resulting significant savings.


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Citation Formats
C. Eser, “Optimum design of steel structures via artificial bee colony (abc) algorithm and SAP2000,” M.S. - Master of Science, Middle East Technical University, 2014.