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Article
Publication date: 1 March 1984

B.H.V. Topping and D.J. Robinson

The use of three non‐linear mathematical programming techniques for the optimization of structural design problems is discussed. The methods — sequential linear…

Abstract

The use of three non‐linear mathematical programming techniques for the optimization of structural design problems is discussed. The methods — sequential linear programming, the feasible direction method and the sequential unconstrained minimization technique — are applied to a portal frame problem to enable a study of their convergence efficiency to be studied. These methods are used for both the sizing of the structural members and determining the optimum roof pitch. The sequential linear programming method is shown to be particularly efficient for application to structural design problems. Some comments on the development of computer software for structural optimization are also given.

Details

Engineering Computations, vol. 1 no. 3
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 1 May 1995

E.H. Mathews and P.A.J. Köhler

The design of optimum pipe and duct networks with available proceduresis difficult, if not impossible. A more efficient procedure that willautomatically produce the…

Abstract

The design of optimum pipe and duct networks with available procedures is difficult, if not impossible. A more efficient procedure that will automatically produce the optimum design is required. Such a procedure is presented in this article. The design is formulated as a constrained nonlinear optimization problem. This problem is solved using a unique numerical optimization algorithm. The solution entails the calculation of the cross sectional dimensions of the ducts and pipes so that the life cycle cost of the network is minimized. The topology equations are derived using graph theory thereby allowing complex networks with loops to be designed numerically. A duct network consisting of a fan and 35 duct sections is designed according to certain specifications. Using the proposed procedure optimum designs were obtained within seconds on a 33 MHz 486 micro‐computer. The procedure was further applied to the optimization of a coal pipeline. It is shown that the optimized solution will cost 14% ($8 million) less than the previous design with conventional design techniques.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 5 no. 5
Type: Research Article
ISSN: 0961-5539

Keywords

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Abstract

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Handbook of Transport Strategy, Policy and Institutions
Type: Book
ISBN: 978-0-0804-4115-3

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Article
Publication date: 1 August 2005

A. Benabidallah and Y. Cherruault

To study constrained or unconstrained global optimization problems in a cube of Rd where d is a positive integer.

Abstract

Purpose

To study constrained or unconstrained global optimization problems in a cube of Rd where d is a positive integer.

Design/methodology/approach

α‐dense curves are initially used to transform this problem into a global optimization problem of a single variable. The optimization of the one variable is then treated by means of the Legendre‐Fenchel Transform. This discrete convex envelope of the one variable function obtained previously, can then be computed.

Findings

Global optimization problems of this nature have already been extensively studied by the authors. In this paper they have coupled the Alienor method with Legendre‐Fenchel Tranform to compute a discrete convex envelope of the function to minimize. A fast algorithm was successfully used to do this.

Research limitations/implications

This approach to global optimization is based on α‐dense curves and numerical tests performed on a Pentium IV (1,700 MHz) computer used with Mathematica 4 software.

Practical implications

Gives the solutions illustrated in the numerous examples provided that show the practicality of the methodology.

Originality/value

A new approach based on extensive research into global optimization via α‐dense curves.

Details

Kybernetes, vol. 34 no. 7/8
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 27 May 2014

Laxminarayan Sahoo, Asoke Kumar Bhunia and Dilip Roy

– The purpose of this paper is to formulate the reliability optimization problem in stochastic and interval domain and also to solve the same under different stochastic set up.

Abstract

Purpose

The purpose of this paper is to formulate the reliability optimization problem in stochastic and interval domain and also to solve the same under different stochastic set up.

Design/methodology/approach

Stochastic programming technique has been used to convert the chance constraints into deterministic form and the corresponding problem is transformed to mixed-integer constrained optimization problem with interval objective. Then the reduced problem has been converted to unconstrained optimization problem with interval objective by Big-M penalty technique. The resulting problem has been solved by advanced real coded genetic algorithm with interval fitness, tournament selection, intermediate crossover and one-neighbourhood mutation.

Findings

A new optimization technique has been developed in stochastic domain and the concept of interval valued parameters has been integrated with the stochastic setup so as to increase the applicability of the resultant solution to the interval valued nonlinear optimization problems.

Practical implications

The concept of probability distribution with interval valued parameters has been introduced. This concept will motivate the researchers to carry out the research in this new direction.

Originality/value

The application of genetic algorithm is extended to solve the reliability optimization problem in stochastic and interval domain.

Details

International Journal of Quality & Reliability Management, vol. 31 no. 6
Type: Research Article
ISSN: 0265-671X

Keywords

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Article
Publication date: 28 October 2014

Alexander Zemliak

The purpose of this paper is to define the process of analog circuit optimization on the basis of the control theory application. This approach produces many different…

Abstract

Purpose

The purpose of this paper is to define the process of analog circuit optimization on the basis of the control theory application. This approach produces many different strategies of optimization and determines the problem of searching of the best strategy in sense of minimal computer time. The determining of the best strategy of optimization and a searching of possible structure of this strategy with a minimal computer time is a principal aim of this work.

Design/methodology/approach

Different kinds of strategies for circuit optimization have been evaluated from the point of view of operations’ number. The generalized methodology for the optimization of analog circuit was formulated by means of the optimum control theory. The main equations for this methodology were elaborated. These equations include the special control functions that are introduced artificially. This approach generalizes the problem and generates an infinite number of different strategies of optimization. A problem of construction of the best algorithm of optimization is defined as a typical problem of the control theory. Numerical results show the possibility of application of this approach for optimization of electronic circuits and demonstrate the efficiency and perspective of the proposed methodology.

Findings

Examples show that the better optimization strategies that are appeared in limits of developed approach have a significant time gain with respect to the traditional strategy. The time gain increases when the size and the complexity of the optimized circuit are increasing. An additional acceleration effect was used to improve the properties of presented optimization process.

Originality/value

The obtained results show the perspectives of new approach for circuit optimization. A large set of various strategies of circuit optimization serves as a basis for searching the better strategies with a minimum computer time. The gain in processor time for the best strategy reaches till several thousands in comparison with traditional approach.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 33 no. 6
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 28 March 2008

Omer Cansizoglu, Ola L.A. Harrysson, Harvey A. West, Denis R. Cormier and Tushar Mahale

Optimization techniques can be used to design geometrically complex components with a wide variety of optimization criteria. However, such components have been very…

Abstract

Purpose

Optimization techniques can be used to design geometrically complex components with a wide variety of optimization criteria. However, such components have been very difficult and costly to produce. Layered fabrication technologies such as electron beam melting (EBM) open up new possibilities though. This paper seeks to investigate the integration of structural optimization and direct metal fabrication process.

Design/methodology/approach

Mesh structures were designed, and optimization problems were defined to improve structural performance. Finite element analysis code in conjunction with nonlinear optimization routines were used in MATLAB. Element data were extracted from an STL‐file, and output structures from the optimization routine were manufactured using an EBM machine. Original and optimized structures were tested and compared.

Findings

There were discrepancies between the performance of the theoretical structures and the physical EBM structures due to the layered fabrication approach. A scaling factor was developed to account for the effect of layering on the material properties.

Practical implications

Structural optimization can be used to improve the performance of a design, and direct fabrication technologies can be used to realise these structures. However, designers must realize that fabricated structures are not identical to idealized CAD structures, hence material properties much be adjusted accordingly.

Originality/value

Integration of structural optimization and direct metal fabrication was reported in the paper. It shows the process from design through manufacturing with integrated analysis.

Details

Rapid Prototyping Journal, vol. 14 no. 2
Type: Research Article
ISSN: 1355-2546

Keywords

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Article
Publication date: 28 April 2021

Virok Sharma, Mohd Zaki, Kumar Neeraj Jha and N. M. Anoop Krishnan

This paper aims to use a data-driven approach towards optimizing construction operations. To this extent, it presents a machine learning (ML)-aided optimization approach…

Abstract

Purpose

This paper aims to use a data-driven approach towards optimizing construction operations. To this extent, it presents a machine learning (ML)-aided optimization approach, wherein the construction cost is predicted as a function of time, resources and environmental impact, which is further used as a surrogate model for cost optimization.

Design/methodology/approach

Taking a dataset from literature, the paper has applied various ML algorithms, namely, simple and regularized linear regression, random forest, gradient boosted trees, neural network and Gaussian process regression (GPR) to predict the construction cost as a function of time, resources and environmental impact. Further, the trained models were used to optimize the construction cost applying single-objective (with and without constraints) and multi-objective optimizations, employing Bayesian optimization, particle swarm optimization (PSO) and non-dominated sorted genetic algorithm.

Findings

The results presented in the paper demonstrate that the ensemble methods, such as gradient boosted trees, exhibit the best performance for construction cost prediction. Further, it shows that multi-objective optimization can be used to develop a Pareto front for two competing variables, such as cost and environmental impact, which directly allows a practitioner to make a rational decision.

Research limitations/implications

Note that the sequential nature of events which dictates the scheduling is not considered in the present work. This aspect could be incorporated in the future to develop a robust scheme that can optimize the scheduling dynamically.

Originality/value

The paper demonstrates that a ML approach coupled with optimization could enable the development of an efficient and economic strategy to plan the construction operations.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 19 October 2018

Shuanggao Li, Zhengping Deng, Qi Zeng and Xiang Huang

The assembly of large component in out-field is an important part for the usage and maintenance of aircrafts, which is mostly manually accomplished at present, as the…

Abstract

Purpose

The assembly of large component in out-field is an important part for the usage and maintenance of aircrafts, which is mostly manually accomplished at present, as the commonly used large-volume measurement systems are usually inapplicable. This paper aims to propose a novel coaxial alignment method for large aircraft component assembly using distributed monocular vision.

Design/methodology/approach

For each of the mating holes on the components, a monocular vision module is applied to measure the poses of holes, which together shape a distributed monocular vision system. A new unconstrained hole pose optimization model is developed considering the complicated wearing on hole edges, and it is solved by a iterative reweighted particle swarm optimization (IR-PSO) method. Based on the obtained poses of holes, a Plücker line coordinates-based method is proposed for the relative posture evaluation between the components, and the analytical solution of posture parameters is derived. The required movements for coaxial alignment are finally calculated using the kinematics model of parallel mechanism.

Findings

The IR-PSO method derived more accurate hole pose arguments than the state-of-the-art method under complicated wearing situation of holes, and is much more efficient due to the elimination of constraints. The accuracy of the Plücker line coordinates-based relative posture evaluation (PRPE) method is competitive with the singular value decomposition (SVD) method, but it does not rely on the corresponding of point set; thus, it is more appropriate for coaxial alignment.

Practical implications

An automatic coaxial alignment system (ACAS) has been developed for the assembly of a large pilotless aircraft, and a coaxial error of 0.04 mm is realized.

Originality/value

The IR-PSO method can be applied for pose optimization of other cylindrical object, and the analytical solution of Plücker line coordinates-based axes registration is derived for the first time.

Details

Assembly Automation, vol. 38 no. 4
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 5 October 2015

Daniele Peri

The purpose of this paper is to propose a modification of the original PSO algorithm in order to avoid the evaluation of the objective function outside the feasible set…

Abstract

Purpose

The purpose of this paper is to propose a modification of the original PSO algorithm in order to avoid the evaluation of the objective function outside the feasible set, improving the parallel performances of the algorithm in the view of its application on parallel architectures.

Design/methodology/approach

Classical PSO iteration is repeated for each particle until a feasible point is found: the global search is performed by a set of independent sub-iteration, at the particle level, and the evaluation of the objective function is performed only once the full swarm is feasible. After that, the main attractors are updated and a new sub-iteration is initiated.

Findings

While the main qualities of PSO are preserved, a great advantage in terms of identification of the feasible region and detection of the best feasible solution is obtained. Furthermore, the parallel structure of the algorithm is preserved, and the load balance improved. The results of the application to real-life optimization problems, where constraint satisfaction sometime represents a problem itself, gives the measure of this advantage: an improvement of about 10 percent of the optimal solution is obtained by using the modified version of the algorithm, with a more precise identification of the optimal design variables.

Originality/value

Differently from the standard approach, utilizing a penalty function in order to discharge unfeasible points, here only feasible points are produced, improving the exploration of the feasible region and preserving the parallel structure of the algorithm.

Details

Engineering Computations, vol. 32 no. 7
Type: Research Article
ISSN: 0264-4401

Keywords

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