Evaluation of recent metaheuristic search rechniques in optimum design of steel structures

Date

2023-4-26

Author

Kalaycı, Ahmet Eray

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Meta-heuristic search techniques have become popular in the last decade due to advantages, such as preventing local optimum solutions and producing discrete solutions to structural systems. The main purpose of the optimization techniques is to achieve the minimum weight or cost design of a structural system. As there are so many decision variables while calculating the weight or cost of a structure, structural optimization is carried out to find the best design out of a large set of acceptable solutions. Five optimization techniques; namely Atomic Orbital Search, Honey Badger Algorithm, Nuclear Fission-Nuclear Fusion Algorithm, Pathfinder Algorithm, and Salp Swarm Algorithm are used in this study to optimize the investigated benchmark problems and structural test problems taken from the literature. These algorithms are initiated randomly, but each of them has different improvement steps to reach the optimum result. In this study, the results obtained with all these five different metaheuristic algorithms are compared with each other and also with the formerly reported solutions of the investigated problems in the previous studies.

Subject Keywords

Structural Optimization, Salp Swarm Algorithm, Steel Truss Systems, Size Optimization

URI

https://hdl.handle.net/11511/103105

Collections

Graduate School of Natural and Applied Sciences, Thesis