scholarly journals Cost Optimization of Steel-concrete Composite Floor Systems with Castellated Steel Beams

2020 ◽  
Author(s):  
Ali Kaveh ◽  
Amir Fakoor
Keyword(s):  
Cost Function ◽  
Cost Reduction ◽  
Design Theory ◽  
Particle System ◽  
Cost Optimization ◽  
Steel Beams ◽  
Optimization Program ◽  
Accurate Design ◽  
Floor Systems ◽  
The Cost

Performance of cost optimization program of composite steel deck-slabs (DS) and supporting castellated beams (CB) consisting of interior beams, edge beams and girders is proposed in this paper. The program applies the vibrating particle system (VPS) meta-heuristic algorithm, which imitates the free vibration of ideal one-story frame structures with viscous damping. The program is also furnished with an advanced cost function, which takes into account both material and fabrication costs of all parts of the floor system. The effect of four major cost reduction procedures and additional cost-saving techniques are studied on the cost function. Considering various DS profiles, altering the dimensions of hexagonal openings, different number of floor divisions and choosing costlier DSs except the optimal deck are the major cost reduction procedures. Inclusion of partial composite action for CBs, infilling certain openings of CBs and applying camber are the supplementary economizing techniques. To realize the economy of LRFD method, a meticulous design theory of composite CBs in adherence with LRFD principles of AISC 360-16 specifications is applied to the formulation of the strength constraints. Due to excessive deflections and due emphasis on vibration control of CBs, we implement accurate design procedures for the formulation of the serviceability constraints. Performance and superiority of the proposed optimization program is validated by studying three distinct real-size design examples taken from the literatures.

scholarly journals Cost optimization and sensitivity analysis of composite beams

2016 ◽  
Vol 2 (2) ◽  
pp. 52-62 ◽  
Author(s):  
Hamid Eskandari ◽  
Tahereh Korouzhdeh
Keyword(s):  
Concrete Slab ◽  
Cost Optimization ◽  
Cost Savings ◽  
Composite Beams ◽  
Steel Beams ◽  
Slab Thickness ◽  
Shear Connectors ◽  
Factor Design ◽  
Load And Resistance Factor ◽  
The Cost

This study presents exact solution analysis for the cost optimization of Composite Beams (CB) based on the Load and Resistance Factor Design (LRFD) specifications. Matlab code formulation is applied to analysis of sensitivity for various parameters such as cost of concrete, steel beam, span length, concrete slab thickness, compressive strength of concrete, steel beams space and shear connectors on CB. Almost 20 thousands design were analysed to obtain various contour which be found that it is feasible, efficient and effective and capable in optimization of composite beam designs.The obtained results represent that many of the contour are capable by achieving substantial cost savings for composite materials. Therefore, the analysis can be developed for practical designs to structural designers. A parametric study was also conducted to investigate the effects of IPE, IPB, INP profiles, UNP size and thickness of slabs and beam length on the cost optimization of CB.

scholarly journals The Influence of Main Design Parameters on the Overall Cost of a Gearbox

2020 ◽  
Vol 10 (7) ◽  
pp. 2365 ◽  
Author(s):  
Ngoc-Pi Vu ◽  
Dinh-Ngoc Nguyen ◽  
Anh-Tung Luu ◽  
Ngoc-Giang Tran ◽  
Thi-Hong Tran ◽  
...  
Keyword(s):  
Simulation Experiment ◽  
Cost Optimization ◽  
Design Parameters ◽  
Regression Equations ◽  
Main Design ◽  
Optimization Program ◽  
The Third ◽  
Input Parameters ◽  
The Cost ◽  
Total Ratio

This study is aimed at determining optimum partial gear ratios to minimize the cost of a three-stage helical gearbox. In this work, eleven input parameters were investigated to find their influence on the optimum gear ratios of the second and the third stages ( u 2 and u 3 ). To reach the goal, a simulation experiment was designed and implemented by a cost optimization program. The results revealed that in addition to the input parameters, their interactions also have important effects in which the total ratio gearbox ratio ( u t ) and the cost of shaft ( C s ) have the most impact on u 2 and u 3 responses, respectively. Moreover, the proposed models of the two responses are highly consistent to the experimental results. The proposed regression equations can be applied to solve optimization cost problems.

Implementasi Analisis Proses Bisnis Sebagai Upaya Pengurangan Biaya

2019 ◽  
Vol 10 (1) ◽  
pp. 1-27
Author(s):  
Aniek Wijayanti
Keyword(s):  
Business Process ◽  
Cost Reduction ◽  
Process Analysis ◽  
Value Added ◽  
Added Value ◽  
Natural Material ◽  
Management Activity ◽  
Procurement Process ◽  
Material Procurement ◽  
The Cost

Business Process Analysis can be used to eliminate or reduce a waste cost caused by non value added activities that exist in a process. This research aims at evaluating activities carried out in the natural material procurement process in the PT XYZ, calculating the effectiveness of the process cycle, finding a way to improve the process management, and calculating the cost reduction that can achieved by activity management. A case study was the approach of this research. The researcher obtained research data throughout deep interviews with the staff who directly involved in the process, observation, and documentation of natural material procurement. The result of this study show that the effectiveness of the process cycle of natural material procurement in the factory reached as much as 87,1% for the sand material and 72% for the crushed stone. This indicates that the process still carry activities with no added value and still contain ineffective costs. Through the Business Process Mechanism, these non value added activities can be managed so that the process cycle becomes more efficient and cost effectiveness is achieved. The result of the effective cycle calculation after the management activities implementation is 100%. This means that the cost of natural material procurement process has become effective. The result of calculation of the estimated cost reduction as a result of management activity is as much as Rp249.026.635,90 per year.

ANALISIS PENGARUH BIAYA OPERASIONAL PADA PERUSAHAAN PENERBANGAN NASIONAL

2017 ◽  
Vol 1 (2) ◽  
pp. 81-107
Author(s):  
Dheny Biantara
Keyword(s):  
Value Chain ◽  
Cost Efficiency ◽  
Cost Reduction ◽  
Cost Leadership ◽  
Oil Pricing ◽  
The Cost ◽  
Operation Flexibility ◽  
Airline Maintenance

Summarized Indonesian airline executive views on the reason for the cost problem in mayor airline andon the potential areas and measures of cost reduction in airline operation. Present an introductionsurvey where 3 executives from 3 Indonesian airlines were respondent. In the executive opinion the costproblem in mayor Indonesian airline is primarily due to fuel and oil pricing and money currency. Of thevarious function in airline maintenance was seen as least cost efficiency, whereas flight operation wasseen as an area with most potential for cost reduction. Indonesian airline had made route and fleetchanges after the beginning of 2011 to reduce cost, concludes from the analisys result havingprivatization would be an important step towards more efficient airline operation. Flexibility fromIndonesian airline regulatory would be very much welcome and the value chain concept to improveIndonesian airline having competitive adventage and cost leadership differentiation.

scholarly journals An Adaptive Optimization Method Based on Learning Rate Schedule for Neural Networks

2021 ◽  
Vol 11 (2) ◽  
pp. 850
Author(s):  
Dokkyun Yi ◽  
Sangmin Ji ◽  
Jieun Park
Keyword(s):  
Artificial Intelligence ◽  
Cost Function ◽  
Numerical Experiments ◽  
Global Minimum ◽  
Optimization Method ◽  
Learning Method ◽  
Adaptive Optimization ◽  
The Cost ◽  
Proof Of Convergence ◽  
Learning Data

Artificial intelligence (AI) is achieved by optimizing the cost function constructed from learning data. Changing the parameters in the cost function is an AI learning process (or AI learning for convenience). If AI learning is well performed, then the value of the cost function is the global minimum. In order to obtain the well-learned AI learning, the parameter should be no change in the value of the cost function at the global minimum. One useful optimization method is the momentum method; however, the momentum method has difficulty stopping the parameter when the value of the cost function satisfies the global minimum (non-stop problem). The proposed method is based on the momentum method. In order to solve the non-stop problem of the momentum method, we use the value of the cost function to our method. Therefore, as the learning method processes, the mechanism in our method reduces the amount of change in the parameter by the effect of the value of the cost function. We verified the method through proof of convergence and numerical experiments with existing methods to ensure that the learning works well.

scholarly journals Development of Optimal Design Method for Steel Double-Beam Floor System Considering Rotational Constraints

2021 ◽  
Vol 11 (7) ◽  
pp. 3266
Author(s):  
Insub Choi ◽  
Dongwon Kim ◽  
Junhee Kim
Keyword(s):  
Optimal Design ◽  
Design Process ◽  
Design Method ◽  
Steel Beams ◽  
High Gravity ◽  
Double Beam ◽  
Iterative Analysis ◽  
Floor Systems ◽  
Optimal Design Method ◽  
Floor System

Under high gravity loads, steel double-beam floor systems need to be reinforced by beam-end concrete panels to reduce the material quantity since rotational constraints from the concrete panel can decrease the moment demand by inducing a negative moment at the ends of the beams. However, the optimal design process for the material quantity of steel beams requires a time-consuming iterative analysis for the entire floor system while especially keeping in consideration the rotational constraints in composite connections between the concrete panel and steel beams. This study aimed to develop an optimal design method with the LM (Length-Moment) index for the steel double-beam floor system to minimize material quantity without the iterative design process. The LM index is an indicator that can select a minimum cross-section of the steel beams in consideration of the flexural strength by lateral-torsional buckling. To verify the proposed design method, the material quantities between the proposed and code-based design methods were compared at various gravity loads. The proposed design method successfully optimized the material quantity of the steel double-beam floor systems without the iterative analysis by simply choosing the LM index of the steel beams that can minimize objective function while satisfying the safety-related constraint conditions. In particular, under the high gravity loads, the proposed design method was superb at providing a quantity-optimized design option. Thus, the proposed optimal design method can be an alternative for designing the steel double-beam floor system.

Sorting permutations by fragmentation-weighted operations

2020 ◽  
Vol 18 (02) ◽  
pp. 2050006 ◽  
Author(s):  
Alexsandro Oliveira Alexandrino ◽  
Carla Negri Lintzmayer ◽  
Zanoni Dias
Keyword(s):  
Approximation Algorithms ◽  
Computational Biology ◽  
Cost Function ◽  
Traditional Approach ◽  
Upper Bounds ◽  
Evolutionary Distance ◽  
Lower And Upper Bounds ◽  
Approximation Factor ◽  
New Type ◽  
The Cost

One of the main problems in Computational Biology is to find the evolutionary distance among species. In most approaches, such distance only involves rearrangements, which are mutations that alter large pieces of the species’ genome. When we represent genomes as permutations, the problem of transforming one genome into another is equivalent to the problem of Sorting Permutations by Rearrangement Operations. The traditional approach is to consider that any rearrangement has the same probability to happen, and so, the goal is to find a minimum sequence of operations which sorts the permutation. However, studies have shown that some rearrangements are more likely to happen than others, and so a weighted approach is more realistic. In a weighted approach, the goal is to find a sequence which sorts the permutations, such that the cost of that sequence is minimum. This work introduces a new type of cost function, which is related to the amount of fragmentation caused by a rearrangement. We present some results about the lower and upper bounds for the fragmentation-weighted problems and the relation between the unweighted and the fragmentation-weighted approach. Our main results are 2-approximation algorithms for five versions of this problem involving reversals and transpositions. We also give bounds for the diameters concerning these problems and provide an improved approximation factor for simple permutations considering transpositions.

Maximum Likelihood Ensemble Filter: Theoretical Aspects

2005 ◽  
Vol 133 (6) ◽  
pp. 1710-1726 ◽  
Author(s):  
Milija Zupanski
Keyword(s):  
Maximum Likelihood ◽  
Data Assimilation ◽  
Cost Function ◽  
Ensemble Data Assimilation ◽  
Error Covariance ◽  
Ensemble Data ◽  
Analysis Error ◽  
Nonlinear Observation ◽  
The Cost ◽  
Maximum Likelihood Ensemble Filter

Abstract A new ensemble-based data assimilation method, named the maximum likelihood ensemble filter (MLEF), is presented. The analysis solution maximizes the likelihood of the posterior probability distribution, obtained by minimization of a cost function that depends on a general nonlinear observation operator. The MLEF belongs to the class of deterministic ensemble filters, since no perturbed observations are employed. As in variational and ensemble data assimilation methods, the cost function is derived using a Gaussian probability density function framework. Like other ensemble data assimilation algorithms, the MLEF produces an estimate of the analysis uncertainty (e.g., analysis error covariance). In addition to the common use of ensembles in calculation of the forecast error covariance, the ensembles in MLEF are exploited to efficiently calculate the Hessian preconditioning and the gradient of the cost function. A sufficient number of iterative minimization steps is 2–3, because of superior Hessian preconditioning. The MLEF method is well suited for use with highly nonlinear observation operators, for a small additional computational cost of minimization. The consistent treatment of nonlinear observation operators through optimization is an advantage of the MLEF over other ensemble data assimilation algorithms. The cost of MLEF is comparable to the cost of existing ensemble Kalman filter algorithms. The method is directly applicable to most complex forecast models and observation operators. In this paper, the MLEF method is applied to data assimilation with the one-dimensional Korteweg–de Vries–Burgers equation. The tested observation operator is quadratic, in order to make the assimilation problem more challenging. The results illustrate the stability of the MLEF performance, as well as the benefit of the cost function minimization. The improvement is noted in terms of the rms error, as well as the analysis error covariance. The statistics of innovation vectors (observation minus forecast) also indicate a stable performance of the MLEF algorithm. Additional experiments suggest the amplified benefit of targeted observations in ensemble data assimilation.

Using the cost function to generate Marshallian demand systems

2000 ◽  
Vol 25 (2) ◽  
pp. 209-227 ◽  
Author(s):  
Keith R. McLaren ◽  
Peter D. Rossitter ◽  
Alan A. Powell
Keyword(s):  
Cost Function ◽  
Demand Systems ◽  
The Cost
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