2013
DOI: 10.1260/1369-4332.16.6.1035
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Upper Bound Strategy in Optimum Design of Truss Structures: A Big Bang-Big Crunch Algorithm Based Application

Abstract: One main shortcoming of metaheuristic search techniques in structural optimization is the large number of time-consuming structural analyses required for convergence to a reasonable solution. This study is an attempt to apply the so-called upper bound strategy (UBS) as a simple, yet an efficient strategy to reduce the total number of structural analyses through avoiding unnecessary analyses during the course of optimization. Although, the usefulness of the UBS is demonstrated in conjunction with a big bang-big… Show more

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Cited by 20 publications
(27 citation statements)
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“…The HFSA, HFHS and HFBBBC algorithms developed in this study for mechanical identification problems were tested on two composite structures and a hyperelastic biological membrane. They were compared with other SA/HS/BBBC variants (e.g., [77,81,83,84] and their successive enhancements [162,163,164,165,166]) including gradient information in the optimization search, as well as with adaptive harmony search [170,171], big bang-big crunch with upper bound strategy (BBBC-UBS) [172], JAYA [35], MATLAB Sequential Quadratic Programming (MATLAB-SQP) [173] and ANSYS built-in optimization routines [174]. The ANSYS built-in optimization routines (e.g., gradient-based, zero order and response surface approximation) were run in cascade or alternated in order to maximize their efficiency.…”
Section: Test Problems and Resultsmentioning
confidence: 99%
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“…The HFSA, HFHS and HFBBBC algorithms developed in this study for mechanical identification problems were tested on two composite structures and a hyperelastic biological membrane. They were compared with other SA/HS/BBBC variants (e.g., [77,81,83,84] and their successive enhancements [162,163,164,165,166]) including gradient information in the optimization search, as well as with adaptive harmony search [170,171], big bang-big crunch with upper bound strategy (BBBC-UBS) [172], JAYA [35], MATLAB Sequential Quadratic Programming (MATLAB-SQP) [173] and ANSYS built-in optimization routines [174]. The ANSYS built-in optimization routines (e.g., gradient-based, zero order and response surface approximation) were run in cascade or alternated in order to maximize their efficiency.…”
Section: Test Problems and Resultsmentioning
confidence: 99%
“…The abovementioned comparison should be considered very indicative for the following reasons: Adaptive HS [170,171] and BBBC-UBS [172] represent state-of-the-art formulations of harmony search and big bang-big crunch, which have been successfully utilized in many optimization problems. In particular, the adaptive HS algorithm adaptively changes internal parameters without any intervention by the user: this approach is very similar to what is done by HFHS.…”
Section: Test Problems and Resultsmentioning
confidence: 99%
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“…The total number of structural analysis required to reach the optimum design is large similar to most of metaheuristic algorithms. This number can be reduced by carrying out some enhancement in the algorithm, such as adding upper bound strategy (UBS) [21,42,43], as a future work. The idea behind UBS is to detect those candidate designs which have no chance to improve the search during the optimization process.…”
Section: Numerical Examplesmentioning
confidence: 99%
“…Hasançebi and Azad (2013) presented a new redistribution equation for size optimization of skeletal structures. Azad et al (2013) proposed the Upper Bound Strategy (UBS) to reduce the number of analyses and validated the performance of their strategy with various trusssizing problems. Another hybrid algorithm is presented by Kaveh and Mahdavi (2013) for size optimization of trusses with multiple frequency constraints.…”
Section: Introductionmentioning
confidence: 99%