Optimal design of timber-concrete composite floors based on the multi-parametric MINLP optimization

Jelušič, Primož; Kravanja, Stojan

doi:10.1016/j.compstruct.2017.07.062

Cited by 25 publications

(12 citation statements)

References 31 publications

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“…Sharafi et al [123] used an objective function that minimizes the material cost and formwork cost simultaneously for the optimal design of continuous reinforced concrete beams. Some researchers also apply parametric mixed-integer non-linear programming (MINLP) approach in structural optimization for cost (or mass) minimization [124][125][126], which is a mathematical programming technique that simultaneously optimizes the discrete system structure and continuous parameters with nonlinear objective functions and constrains [127]. The algorithms for MINLP approach are usually designed for handling large-scale, highly combinatorial and highly nonlinear problems, such as outer approximation/equality-relaxation (OA/ER) algorithm and generalized Bender's decomposition (GBD) algorithm [127].…”

Section: Quantification Of Optimization Objectivesmentioning

confidence: 99%

Structural Optimization in Civil Engineering: A Literature Review

Mei

Wang

2021

Buildings

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Since tremendous resources are consumed in the architecture, engineering, and construction (AEC) industry, the sustainability and efficiency in this field have received increasing concern in the past few decades. With the advent and development of computational tools and information technologies, structural optimization based on mathematical computation has become one of the most commonly used methods for the sustainable and efficient design in the field of civil engineering. However, despite the wide attention of researchers, there has not been a critical review of the recent research progresses on structural optimization yet. Therefore, the main objective of this paper is to comprehensively review the previous research on structural optimization, provide a thorough analysis on the optimization objectives and their temporal and spatial trends, optimization process, and summarize the current research limitations and recommendations of future work. The paper first introduces the significance of sustainability and efficiency in the AEC industry as well as the background of this review work. Then, relevant articles are retrieved and selected, followed by a statistical analysis of the selected articles. Thereafter, the selected articles are analyzed regarding the optimization objectives and their temporal and spatial trends. The four major steps in the structural optimization process, including structural analysis and modelling, formulation of optimization problems, optimization techniques, and computational tools and design platforms, are also reviewed and discussed in detail based on the collected articles. Finally, research gaps of the current works and potential directions of future works are proposed. This paper critically reviews the achievements and limitations of the current research on structural optimization, which provide guidelines for future research on structural optimization in the field of civil engineering.

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Section: Quantification Of Optimization Objectivesmentioning

confidence: 99%

Structural Optimization in Civil Engineering: A Literature Review

Mei

Wang

2021

Buildings

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“…While C Lj stands for the hourly labor costs [€/h], t j [h] are times required for (jJ: placing, curing and vibrating of concrete, cutting and placing the reinforcement, and paneling the concrete beam; cutting, welding, painting the steel beam, and impregnating and painting the timber beam), and f O is an indirect cost factor for overheads (f O = 2). For more information about cost items used in the economic objective function [11] and [12]  …”

Section: Cantilever Beammentioning

confidence: 99%

Sustainable Synthesis and Optimization of Engineering Systems

Bogataj

Čuček

Žula

et al. 2018

WIT Transactions on the Built Environment

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The solutions to engineering systems should not only be feasible but should also be beneficial to all the pillars of sustainable development (economic, environmental and social) to the greatest possible extent. However, due to the inherent trade-offs among the three components of sustainable development, identifying such solutions is not a straightforward task. In this manuscript, we present a simultaneous approach for sustainable synthesis and optimization of engineering systems based on a mixed-integer (non)linear programming MI(N)LP. The approach aims at providing sustainable solutions and an insight into the trade-offs among the economic, environmental and social component of sustainable development. Maximization of a sustainability profit, which is a composite criterion comprised of economic, eco-and social profits, is applied in order to obtain the optimal sustainable solutions. The solutions are compared to those obtained by maximizing either pure economic profit or minimizing Green House Gas emissions. The approach is tested on two case studies and the results are compared. The first example is a simple example from the field of civil engineering. The example presents the synthesis/optimization of a 5.5 meters long cantilever beams. The second example represents supply chain synthesis/optimisation of a biogas production plant in Slovenia. The results for the first case study indicate that 23% increase in sustainability profit causes slight decrease in economic profit (6%). On the other hand, the results for the second case study indicate that a slight increase in sustainability profit (6%) causes a 27% decrease in economic profit. Nevertheless, the solutions obtained by maximizing the sustainability profit remain economically viable due to its composite nature that properly captures and reflects the trade-offs.

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“…A number of problems in the area of structural optimization were solved with the presented MINLP approach: e.g. hydraulic steel gates for dams and hydro-power plants by Kravanja et al [15,16], steel and aluminum trusses by Šilih et al [18], timber truss structures by Šilih et al [19,20], multi-storey steel frame buildings by Klanšek et al [21], single-storey industrial steel buildings by Kravanja and Žula [22] and Kravanja et al [23], composite I-beam structures from concrete and steel by Kravanja and Šilih [24], Klanšek and Kravanja [25,26], Žula et al [27] and Kravanja et al [28] as well as timber-concrete composite floors by Jelušič and Kravanja [29]. A recent research work is also referred in the field of MINLP optimization of project schedules by Klanšek [30] and Cajzek and Klanšek [31].…”

Section: Minmentioning

confidence: 99%

Mixed-integer Non-linear Programming in Civil Engineering

Kravanja¹

2018

Civil Engineering

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The paper discusses the Mixed-Integer Non-linear Programming (MINLP) of problems in civil engineering. The MINLP enables the optimization of continuous parameters simultaneously with discrete alternatives. While continuous parameters are in structural optimization structural costs, masses, loads, stresses, resistances and deflections, as well as the discrete alternatives are in most cases defined as different topologies, standard sizes and materials. The continuous parameters are in the models expressed by continuous variables, whilst the discrete alternatives by discrete (0-1) variables. The MINLP optimization of a structure is usually a comprehensive and highly non-linear calculation process. The MINLP approach requires that a structure is generated as an MINLP superstructure including a number of structure alternatives. One of them is the optimal one. For each optimization problem/structure, an MINLP optimization model of the structure must be developed, where the cost or mass objective function of the structure is subjected to structural analysis and dimensioning equality/inequality constraints. The Modified Outer-Approximation/Equality-Relaxation algorithm and a threephase MINLP strategy are applied. Three numerical examples, i.e. the MINLP optimization of a cantilever beam, composite floor and high-pressure penstock are presented at the end of the paper.

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Optimal design of timber-concrete composite floors based on the multi-parametric MINLP optimization

Cited by 25 publications

References 31 publications

Structural Optimization in Civil Engineering: A Literature Review

Structural Optimization in Civil Engineering: A Literature Review

Sustainable Synthesis and Optimization of Engineering Systems

Mixed-integer Non-linear Programming in Civil Engineering

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