Layout Design of Beam–Slab Floors by a Genetic Algorithm

Nanakorn, Pruettha; Nimtawat, Anan

doi:10.1016/b978-0-12-398364-0.00007-3

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…How to improve the plate yield rate, enhance enterprise competitiveness in the market has become the enterprises are facing problems [5][6][7][8][9][10] . Slab size design [11][12][13][14][15] is an important element for yield rate of steel plates. The current steel industries generally follow two principles, the maximum output and the priority slab type.…”

Section: Introductionmentioning

confidence: 99%

Method of Slab Size Design Based on Maximum Yield Rate of Plates

Song¹,

Shen

Zhang³

et al. 2011

AMR

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To improve the yield rate of steel plates, a method of slab size design is proposed based on maximum yield rate of plates. It includes material transformations algorithm and optimization of slab selection. Many factors are considered in the model covering the equipment capacity, spread rate, compression rate, burning loss and cutting loss. Initially, all possible types of slabs are obtained through material transformations algorithm after the order input. This allows the eventual determination of the slabs of the largest yield rate through the optimization of slab selection. The experiments prove that the model can reduce a number of materials and lessen the pressure of the inventory. An effective increase of plate yield can be expected to improve the economic efficiency of enterprise.

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Section: Introductionmentioning

confidence: 99%

Method of Slab Size Design Based on Maximum Yield Rate of Plates

Song¹,

Shen

Zhang³

et al. 2011

AMR

View full text Add to dashboard Cite

show abstract

Analysis and testing of different penalty function methods and genetic algorithm for solving beam-slab layout design problem

Shailender,

Ahirwal

2023

2nd International Conference on Recent Advances in Computational Techniques

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Compatible Swarm Intelligence Model and Construction Method to Satisfy Bridge Design and Load Rating Requirements and Considering Geotechnical Variability

Harden

Lozano

2022

Transportation Research Record: Journal of the Transportation R

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This paper details the novel combination of a population-based swarm intelligence algorithm, structure mechanics, geotechnical variability, and a specific construction staging methodology, to propose an autonomous construction system which can erect a bridge over arbitrary crossing geometry while satisfying project constraints and conventional design code requirements (the Proposal). The fields of metaheuristic applications in structures (MAS), unmanned aerial systems (UAS), and additive manufacturing are all independent innovations in the transportation industry. The Proposal brings these fields together, with a vision that independent drone robots with very basic programming could construct a bridge with no user interruption and without performing a conventional structural design. A simulation as proof-of-concept is compared with a modern bridge design; the result is a modest increase in materials with an anticipated dramatic saving in labor. The paper also studies the effects of geotechnical variability for insight into preparation for possible future construction methodologies and algorithms. The Proposal has promise where socio-economic issues may be a factor, such as construction of infrastructure in remote locations or developing nations, and emergency repair or replacement of bridges. With recent U.S. policy supporting a permanent lunar presence and expanding Moon to Mars exploration through the Artemis program, the Proposal may also assist infrastructure development in advance of human missions.

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Layout Design of Beam–Slab Floors by a Genetic Algorithm

Cited by 3 publications

References 16 publications

Method of Slab Size Design Based on Maximum Yield Rate of Plates

Method of Slab Size Design Based on Maximum Yield Rate of Plates

Analysis and testing of different penalty function methods and genetic algorithm for solving beam-slab layout design problem

Compatible Swarm Intelligence Model and Construction Method to Satisfy Bridge Design and Load Rating Requirements and Considering Geotechnical Variability

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