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Book part

Nima Gerami Seresht, Rodolfo Lourenzutti, Ahmad Salah and Aminah Robinson Fayek

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes…

Abstract

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Details

Fuzzy Hybrid Computing in Construction Engineering and Management
Type: Book
ISBN: 978-1-78743-868-2

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Article

Yuan Ren, Pingyuan Cui and Enjie Luan

This paper aims to investigate, a new optimization algorithm for complex orbit transfer missions with low‐thrust propulsion system, which minimizes the drawbacks of…

Abstract

Purpose

This paper aims to investigate, a new optimization algorithm for complex orbit transfer missions with low‐thrust propulsion system, which minimizes the drawbacks of traditional optimization methods, such as bad convergence, difficulty of initial guesses and local optimality.

Design/methodology/approach

First, the trajectory optimization problem comes down to a nonlinear constraint parameter optimization by using the concept of traditional hybrid method. Then, one utilizes genetic algorithm (GA) to solve this parameter optimization problem after treating the constraints with the simulated annealing (SA) and random penalty function. Finally, one makes use of localized optimization to improve the precision of the final solutions.

Findings

This algorithm not only keeps the advantages of traditional hybrid method such as high precision and smooth solutions, but also inherits the merits of GA which could avoid initial guess work and obtain a globally optimal solution.

Research limitations/implications

Further, research is required to reduce the computational complexity when the transfer trajectory is very complex and/or has many adjustable variables.

Practical implications

By using this method, the globally optimal solutions of some complex missions, which could not be obtained by traditional method, could be found.

Originality/value

This method combines the GA with traditional hybrid method, and utilizes SA and random penalty functions to treat with constraints, and then gives out a super convergence way to find the globally optimal low‐thrust transfer orbit.

Details

Aircraft Engineering and Aerospace Technology, vol. 79 no. 3
Type: Research Article
ISSN: 0002-2667

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Article

Amir Tjolleng, Kihyo Jung, Hyunsook Han, Hyunjung Han and Jayoung Cho

Size fit and economic efficiency are two crucial aspects that need to be considered in designing a sizing system. However, there could exist a trade-off between those…

Abstract

Purpose

Size fit and economic efficiency are two crucial aspects that need to be considered in designing a sizing system. However, there could exist a trade-off between those aspects in order to establish a practical sizing system. The purpose of this paper is to develop a sequential hybrid method of grid and optimization to generate a practical sizing system using anthropometric data.

Design/methodology/approach

The proposed sequential hybrid method consisted of two sequential steps, which employs grid method and optimization method. In the initial step, the grid method creates primary grids that accommodate a designated percentage (e.g. 90%) of users with best size fit. In the subsequent step, the optimization method generated additional grids to provide acceptable fit, with minimum fit penalty scores for users unaccommodated by the primary grids. Our method was applied to the development of a sizing system for men's military jackets. The proposed method performances were evaluated in terms of accommodation percentage, size fit and number of sizing categories.

Findings

Our proposed method resulted in 26 primary grids during the initial step, which cover 90% of users. Next, we generated six additional grids during the subsequent step that provide minimum fit penalty scores for the rest (10%) users.

Originality/value

The main contributions of this paper are as follows: consider accommodation percentage, size fit and number of sizing categories in the design of sizing system; combine the grid and optimization methods and evaluate a sizing system for men's military jackets. The proposed method is applicable to develop optimal sizing systems for multiple-size products.

Details

International Journal of Clothing Science and Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0955-6222

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Article

Xiwen Cai, Haobo Qiu, Liang Gao, Xiaoke Li and Xinyu Shao

This paper aims to propose hybrid global optimization based on multiple metamodels for improving the efficiency of global optimization.

Abstract

Purpose

This paper aims to propose hybrid global optimization based on multiple metamodels for improving the efficiency of global optimization.

Design/methodology/approach

The method has fully utilized the information provided by different metamodels in the optimization process. It not only imparts the expected improvement criterion of kriging into other metamodels but also intelligently selects appropriate metamodeling techniques to guide the search direction, thus making the search process very efficient. Besides, the corresponding local search strategies are also put forward to further improve the optimizing efficiency.

Findings

To validate the method, it is tested by several numerical benchmark problems and applied in two engineering design optimization problems. Moreover, an overall comparison between the proposed method and several other typical global optimization methods has been made. Results show that the global optimization efficiency of the proposed method is higher than that of the other methods for most situations.

Originality/value

The proposed method sufficiently utilizes multiple metamodels in the optimizing process. Thus, good optimizing results are obtained, showing great applicability in engineering design optimization problems which involve costly simulations.

Details

Engineering Computations, vol. 35 no. 1
Type: Research Article
ISSN: 0264-4401

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Article

Luciano Andrea Catalano, Domenico Quagliarella and Pier Luigi Vitagliano

The purpose of this paper is to propose an accurate and efficient technique for computing flow sensitivities by finite differences of perturbed flow fields. It relies on…

Abstract

Purpose

The purpose of this paper is to propose an accurate and efficient technique for computing flow sensitivities by finite differences of perturbed flow fields. It relies on computing the perturbed flows on coarser grid levels only: to achieve the same fine-grid accuracy, the approximate value of the relative local truncation error between coarser and finest grids unperturbed flow fields, provided by a standard multigrid method, is added to the coarse grid equations. The gradient computation is introduced in a hybrid genetic algorithm (HGA) that takes advantage of the presented method to accelerate the gradient-based search. An application to a classical transonic airfoil design is reported.

Design/methodology/approach

Genetic optimization algorithm hybridized with classical gradient-based search techniques; usage of fast and accurate gradient computation technique.

Findings

The new variant of the prolongation operator with weighting terms based on the volume of grid cells improves the accuracy of the MAFD method for turbulent viscous flows. The hybrid GA is capable to efficiently handle and compensate for the error that, although very limited, is present in the multigrid-aided finite-difference (MAFD) gradient evaluation method.

Research limitations/implications

The proposed new variants of HGA, while outperforming the simple genetic algorithm, still require tuning and validation to further improve performance.

Practical implications

Significant speedup of CFD-based optimization loops.

Originality/value

Introduction of new multigrid prolongation operator that improves the accuracy of MAFD method for turbulent viscous flows. First application of MAFD evaluation of flow sensitivities within a hybrid optimization framework.

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Article

M. Grujicic, G. Arakere, P. Pisu, B. Ayalew, Norbert Seyr, Marc Erdmann and Jochen Holzleitner

Application of the engineering design optimization methods and tools to the design of automotive body‐in‐white (BIW) structural components made of polymer metal hybrid

Abstract

Application of the engineering design optimization methods and tools to the design of automotive body‐in‐white (BIW) structural components made of polymer metal hybrid (PMH) materials is considered. Specifically, the use of topology optimization in identifying the optimal initial designs and the use of size and shape optimization techniques in defining the final designs is discussed. The optimization analyses employed were required to account for the fact that the BIW structural PMH component in question may be subjected to different in‐service loads be designed for stiffness, strength or buckling resistance and that it must be manufacturable using conventional injection over‐molding. The paper demonstrates the use of various engineering tools, i.e. a CAD program to create the solid model of the PMH component, a meshing program to ensure mesh matching across the polymer/metal interfaces, a linear‐static analysis based topology optimization tool to generate an initial design, a nonlinear statics‐based size and shape optimization program to obtained the final design and a mold‐filling simulation tool to validate manufacturability of the PMH component.

Details

Multidiscipline Modeling in Materials and Structures, vol. 4 no. 4
Type: Research Article
ISSN: 1573-6105

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Article

Sagar Dnyandev Patil and Yogesh J. Bhalerao

It is seen that little amount of work on optimization of mechanical properties taking into consideration the combined effect of design variables such as stacking angle…

Abstract

Purpose

It is seen that little amount of work on optimization of mechanical properties taking into consideration the combined effect of design variables such as stacking angle, stacking sequence, different resins and thickness of composite laminates has been carried out. The focus of this research work is on the optimization of the design variables like stacking angle, stacking sequence, different resins and thickness of composite laminates which affect the mechanical properties of hybrid composites. For this purpose, the Taguchi technique and the method of gray relational analysis (GRA) are used to identify the optimum combination of design variables. In this case, the effect of the abovementioned design variables, particularly of the newly developed resin (NDR) on mechanical properties of hybrid composites has been investigated.

Design/methodology/approach

The Taguchi method is used for design of experiments and with gray relational grade (GRG) approach, the optimization is done.

Findings

From the experimental analysis and optimization study, it was seen that the NDR gives excellent bonding strength of fibers resulting in enhanced mechanical properties of hybrid composite laminates. With the GRA method, the initial setting (A3B2C4D2) was having GRG 0.866. It was increased by using a new optimum combination (A2B2C4D1) to 0.878. It means that there is an increment in the grade by 1.366%. Therefore, using the GRA approach of analysis, design variables have been successfully optimized to achieve enhanced mechanical properties of hybrid composite laminates.

Originality/value

This is an original research work.

Details

Multidiscipline Modeling in Materials and Structures, vol. 16 no. 6
Type: Research Article
ISSN: 1573-6105

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Article

Panxing Huang, Changzhu Wei, Yuanbei Gu and Naigang Cui

The purpose of this paper is to propose a hybrid optimization approach with high level of solving precision and efficiency for endo-atmospheric ascent trajectory planning…

Abstract

Purpose

The purpose of this paper is to propose a hybrid optimization approach with high level of solving precision and efficiency for endo-atmospheric ascent trajectory planning of launch vehicles.

Design/methodology/approach

Based on the indirect method of optimal control problems, the optimal endo-atmospheric ascent problem with path constraints and final condition constraints is transformed into a Hamiltonian two point boundary value problem (TPBVP). An advanced Gauss pseudo-spectral method is applied to change the Hamiltonian TPBVP into a system of nonlinear algebraic equations, which is solved by a modified Newton method. To guarantee the convergence of the solution, analytical initial guess technology and homotopy technology are also introduced. At last, simulation tests are made.

Findings

The hybrid approach for optimal endo-atmospheric ascent trajectory planning has both fast convergence rate and high solution precision. The simulation results indicate that not only the proposed method is feasible but also it is better than the indirect method, which is a most popular approach for solving the optimal endo-atmospheric ascent problem. Given the same degree of solution accuracy, the new method consumes quite less time on the CPU than that of the indirect method.

Practical implications

The new optimization approach has high level of both solution accuracy and efficiency. It can be used in rapid trajectory designing, on-line trajectory planning and closed-loop guidance of launch vehicles. Also, the proposed Gauss pseudo-spectral method in this paper is a new and efficient method for solving general TPBVPs.

Originality/value

The paper provides a new hybrid optimization method for rapid endo-atmospheric ascent trajectory planning of launch vehicles.

Details

Aircraft Engineering and Aerospace Technology: An International Journal, vol. 88 no. 4
Type: Research Article
ISSN: 1748-8842

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Article

Amit Kumar, Vinod Kumar and Vikas Modgil

The purpose of this paper is to optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm…

Abstract

Purpose

The purpose of this paper is to optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm optimization (BFO-PSO) evolutionary algorithm. For this, a performance model is developed with an objective to analyze the system availability.

Design/methodology/approach

In this paper, a Markov process-based performance model is put forward for system availability estimation. The differential equations associated with the performance model are developed assuming that the failure and repair rate parameters of each sub-system are constant and follow the exponential distribution. The long-run availability expression for the system has been derived using normalizing condition. This mathematical framework is utilized for developing an optimization model in MATLAB 15 and solved through BFO-PSO and basic particle swarm optimization (PSO) evolutionary algorithms coded in the light of applicability. In this analysis, the optimal input parameters are determined for better system performance.

Findings

In the present study, the sensitivity analysis for various sub-systems is carried out in a more consistent manner in terms of the effect on system availability. The optimal failure and repair rate parameters are obtained by solving the performance optimization model through the proposed hybrid BFO-PSO algorithm and hence improved system availability. Further, the results obtained through the proposed evolutionary algorithm are compared with the PSO findings in order to verify the solution. It can be clearly observed from the obtained results that the hybrid BFO-PSO algorithm modifies the solution more precisely and consistently.

Research limitations/implications

There is no limitation for implementation of proposed methodology in complex systems, and it can, therefore, be used to analyze the behavior of the other repairable systems in higher sensitivity zone.

Originality/value

The performance model of the paint manufacturing system is formulated by utilizing the available uncertain data of the used manufacturing unit. Using these data information, which affects the performance of the system are parameterized in the input failure and repair rate parameters for each sub-system. Further, these parameters are varied to find the sensitivity of a sub-system for system availability among the various sub-systems in order to predict the repair priorities for different sub-systems. The findings of the present study show their correspondence with the system experience and highlight the various availability measures for the system analyst in maintenance planning.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 7
Type: Research Article
ISSN: 0265-671X

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Article

P.Di Barba

Introduces papers from this area of expertise from the ISEF 1999 Proceedings. States the goal herein is one of identifying devices or systems able to provide prescribed…

Abstract

Introduces papers from this area of expertise from the ISEF 1999 Proceedings. States the goal herein is one of identifying devices or systems able to provide prescribed performance. Notes that 18 papers from the Symposium are grouped in the area of automated optimal design. Describes the main challenges that condition computational electromagnetism’s future development. Concludes by itemizing the range of applications from small activators to optimization of induction heating systems in this third chapter.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 19 no. 2
Type: Research Article
ISSN: 0332-1649

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