Cost optimization of composite beams using genetic algorithms

Senouci, Ahmed; Al‐Ansari, Mohammed S.

doi:10.1016/j.advengsoft.2009.06.001

Cited by 47 publications

(25 citation statements)

References 9 publications

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“…Such problems include the sizing of individual members (sizing optimization problems), the selection of the most efficient placing of structural members (topology optimization) or a combination of both in order to achieve a single or multiple goals at the same time (multiobjective optimization). The existing literature is rich of papers proposing and applying optimization algorithms in structural problems [62][63][64][65][66][67][68][69][70][71][72][73][74][75][76][77][78].…”

Section: Application On Structural Optimizationmentioning

confidence: 99%

Assessment of the Effectiveness of Cabling System Configuration in Retrofitting Steel-Concrete Composite Buildings

Papavasileiou¹

2017

Proceedings of the 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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Section: Application On Structural Optimizationmentioning

confidence: 99%

Assessment of the Effectiveness of Cabling System Configuration in Retrofitting Steel-Concrete Composite Buildings

Papavasileiou¹

2017

Proceedings of the 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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“…Guerra and Kiousis [64] presented an optimization approach for design of reinforced concrete structures by optimizing the stiffness correlation among all structural members resulting in cost saving compared to typical practice design solutions. Senouci and Ansari [65] presented genetic algorithm based model for cost optimization of composite beams. The objective function is formulated by incorporating the major decision variables affecting the design of composite beams.…”

Section: International Journal Of Computer Applications (0975 -8887) mentioning

confidence: 99%

Applications of Soft Computing in Civil Engineering: A Review

Chandwani¹,

Agrawal²,

Nagar³

2013

IJCA

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The field of engineering is a creative one. The problems encountered in this field are generally unstructured and imprecise influenced by intuitions and past experiences of a designer. The conventional methods of computing relying on analytical or empirical relations become time consuming and labor intensive when posed with real life problems. To study, model and analyze such problems, approximate computer based Soft Computing techniques inspired by the reasoning, intuition, consciousness and wisdom possessed by a human beings are employed. In contrast to conventional computing techniques which rely on exact solutions, soft computing aims at exploiting given tolerance of imprecision, the trivial and uncertain nature of the problem to yield an approximate solution to a problem in quick time. Soft Computing being a multi-disciplinary field uses a variety of statistical, probabilistic and optimization tools which complement each other to produce its three main branches viz., Neural Networks, Genetic Algorithms and Fuzzy Logic. The review paper presents the applications of two major Soft Computing techniques viz., Artificial Neural Networks and Genetic Algorithms in the field of Civil Engineering, which to some extent has replaced the time consuming conventional techniques of computing with intelligent and time saving computing tools.

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“…The problem of the optimal dimensioning of reinforced concrete beams has been considered for many years (Camp et al 2003;Govindaraj, Ramasamy 2005;Senouci, Al-Ansari 2009;Martí, Vidosa 2010;Mohači et al 2010). In this paper, an optimization procedure is given that aims for the adopted cross-section to satisfy the conditions of the ultimate limit state according to the criterion of minimum price of the component materials.…”

Section: Fig 9 Cross-section Of Tested Beamsmentioning

confidence: 99%

Optimization of Uhpfrc Beams Subjected to Bending Using Genetic Algorithms

Ćirović

Радоњанин

Trivunić

et al. 2014

Journal of Civil Engineering and Management

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Abstract. Ultra high performance fibre reinforced concrete (UHPFRC) is cementitious composite with very high strength, and when compared with ordinary concrete it is a more superior material both in terms of its mechanical properties and its durability. In order to predict the behaviour of UHPFRC beams, first of all, experiments were carried out to investigate the mechanical properties of composites containing 2% and 4% of steel fibres. Following this, four beams of 2 m in length were tested by subjecting to four point bending. Two beams contained only micro steel fibres, while the remaining two contained conventional steel bar reinforcement. On the basis of experimental studies and recommendations by the AFGC for UHPC, the behaviour of the beams was modelled and optimization was carried out using genetic algorithms (GA) according to the criterion of minimum price. In this paper, the prices of individual UHPFRC beams are also shown in comparison with beams, which contain steel bars or prestressed reinforcement.Keywords: ultra high performance fibre reinforced concrete, optimization, beams, genetic algorithms. Reference to this paper should be made as follows: Ćirović, G.; Radonjanin, V.; Trivunić, M.; Nikolić, D. 2014. Optimization of UHPFRC beams subjected to bending using genetic algorithms, Journal of Civil Engineering and Management 20(4): 527-536. http://dx

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Cost optimization of composite beams using genetic algorithms

Cited by 47 publications

References 9 publications

Assessment of the Effectiveness of Cabling System Configuration in Retrofitting Steel-Concrete Composite Buildings

Assessment of the Effectiveness of Cabling System Configuration in Retrofitting Steel-Concrete Composite Buildings

Applications of Soft Computing in Civil Engineering: A Review

Optimization of Uhpfrc Beams Subjected to Bending Using Genetic Algorithms

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