Bat inspired algorithm for discrete size optimization of steel frames

Bat inspired (BI) algorithm is a recently developed metaheuristic optimization technique inspired by echolocation behavior of bats. In this study, the BI algorithm is examined in the context of discrete size optimization of steel frames designed for minimum weight. In the optimum design problem frame members are selected from available set of steel sections for producing practically acceptable designs subject to strength and displacement provisions of American Institute of Steel Construction-Allowable Stress Design (AISC-ASD) specification. The performance of the technique is quantified using three real-size large steel frames under actual load and design considerations. The results obtained provide a sufficient evidence for successful performance of the BI algorithm in comparison to other metaheuristics employed in structural optimization.


A bat-inspired algorithm for structural optimization
Hasançebi, Oğuzhan; Pekcan, Onur (Elsevier BV, 2013-11-01)
Bat-inspired (BI) search is a recently developed numerical optimization technique that makes use of echolocation behavior of bats in seeking a design space. This study intends to explore capabilities and potentials of this newly developed method in the realm of structural optimization. A novel algorithm is developed that employs basic principles of this method for structural optimization problems specifically. Performance of the proposed algorithm is measured using one benchmark as well as three practical t...
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Uraz, İrtek; Akın, Serhat; Department of Petroleum and Natural Gas Engineering (2004)
This thesis proposes a framework for determining the optimum location of an injection well by using an inference method, Artificial Neural Networks and a search algorithm to create a search space and locate the global maxima. Theoretical foundation of the proposed framework is followed by description of the field for case study. A complex carbonate reservoir, having a recorded geothermal production history is used to evaluate the proposed framework ( Kizildere Geothermal field, Turkey). In the proposed fram...
Generalized beam angle statistics for shape descrition
Tola, Ömer Önder; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2004)
In this thesis, we introduce a new shape descriptor and a graph based matching algorithm to detect a template shape in an image that contains a single object. The shape descriptor, Generalized Beam Angle Statistics, GBAS is obtained with the generalization of the boundary based shape descriptor, Beam Angle Statistics, BAS
The static stochastic knapsack problem with normally distributed item sizes
Merzifonluoglu, Yasemin; Geunes, Joseph; Romeijn, H. Edwin (Springer Science and Business Media LLC, 2012-09-01)
This paper develops exact and heuristic algorithms for a stochastic knapsack problem where items with random sizes may be assigned to a knapsack. An item's value is given by the realization of the product of a random unit revenue and the random item size. When the realization of the sum of selected item sizes exceeds the knapsack capacity, a penalty cost is incurred for each unit of overflow, while our model allows for a salvage value for each unit of capacity that remains unused. We seek to maximize the ex...
Improving Computational Efficiency of Bat-Inspired Algorithm in Optimal Structural Design
Hasançebi, Oğuzhan (2015-07-01)
Bat-inspired (BI) algorithm is a recent metaheuristic optimization technique that simulates echolocation behavior of bats in seeking a design space. Along the same line with almost all metaheuristics, this algorithm also entails a large number of time-consuming structural analyses in structural design optimization applications. This study is focused on improving computational efficiency of the BI algorithm in optimum structural design. The number of structural analyses required by BI algorithm in the course...
Citation Formats
O. Hasançebi, “Bat inspired algorithm for discrete size optimization of steel frames,” ADVANCES IN ENGINEERING SOFTWARE, pp. 173–185, 2014, Accessed: 00, 2020. [Online]. Available: