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This paper aims to cover the development of a methodology for hybrid fuzzy Monte Carlo agent-based simulation (FMCABS) and its implementation on a parametric study of construction crew performance.

The developed methodology uses fuzzy logic, Monte Carlo simulation and agent-based modeling to simulate the behavior of construction crews and predict their performance. Both random and subjective uncertainties are considered in model variables.

The developed methodology was implemented on a real case involving the parametric study of construction crew performance to assess its applicability and suitability for this context.

This parametric study demonstrates a practical application for the hybrid FMCABS methodology. Though findings from this study are limited to the context of construction crew motivation and performance, the applicability of the developed methodology extends beyond the construction domain.

This paper will help construction practitioners to predict and improve crew performance by taking into account both random and subjective uncertainties.

This paper will advance construction modeling by allowing for the assessment of social interactions among crews and their effects on crew performance.

The developed hybrid FMCABS methodology represents an original contribution, as it allows agent-based models to simultaneously process all types of variables (i.e. deterministic, random and subjective) in the same simulation experiment while accounting for interactions among different agents. In addition, the developed methodology is implemented in a novel and extensive parametric study of construction crew performance.

The purpose of this paper is to propose a new linear-nonlinear data preprocessing-based hybrid model to achieve a more accurate result at a lower cost for wind power forecasting. For this purpose, a decomposed based series-parallel hybrid model (PKF-ARIMA-FMLP) is proposed which can model linear/nonlinear and certain/uncertain patterns in underlying data simultaneously.

To design the proposed model at first, underlying data are divided into two categories of linear and nonlinear patterns by the proposed Kalman filter (PKF) technique. Then, the linear patterns are modeled by the linear-fuzzy nonlinear series (LLFN) hybrid models to detect linearity/nonlinearity and certainty/uncertainty in underlying data simultaneously. This step is also repeated for nonlinear decomposed patterns. Therefore, the nonlinear patterns are modeled by the linear-fuzzy nonlinear series (NLFN) hybrid models. Finally, the weight of each component (e.g. KF, LLFN and NLFN) is calculated by the least square algorithm, and then the results are combined in a parallel structure. Then the linear and nonlinear patterns are modeled with the lowest cost and the highest accuracy.

The effectiveness and predictive capability of the proposed model are examined and compared with its components, based models, single models, series component combination based hybrid models, parallel component combination based hybrid models and decomposed-based single model. Numerical results show that the proposed linear-nonlinear data preprocessing-based hybrid models have been able to improve the performance of single, hybrid and single decomposed based prediction methods by approximately 66.29%, 52.10% and 38.13% for predicting wind power time series in the test data, respectively.

The combination of single linear and nonlinear models has expanded due to the theory of the existence of linear and nonlinear patterns simultaneously in real-world data. The main idea of the linear and nonlinear hybridization method is to combine the benefits of these models to identify the linear and nonlinear patterns in the data in series, parallel or series-parallel based models by reducing the limitations of the single model that leads to higher accuracy, more comprehensiveness and less risky predictions. Although the literature shows that the combination of linear and nonlinear models can improve the prediction results by detecting most of the linear and nonlinear patterns in underlying data, the investigation of linear and nonlinear patterns before entering linear and nonlinear models can improve the performance, which in no paper this separation of patterns into two classes of linear and nonlinear is considered. So by this new data preprocessing based method, the modeling error can be reduced and higher accuracy can be achieved at a lower cost.

This paper has two parts. The purpose of part 1 explains the need for an adaptive paradigm that can efficaciously respond to the complex issues in wicked problems and the fundamentals that this requires were identified. It involved the formulation of a cross-disciplinary relational methodologically plural paradigm with certain properties. The purpose in this Part 2 is to provide a theoretical framework. It adopts autonomous agency theory in which paradigm holders collectively act as “living system” agencies and deliver “living stories” to create coherence in addressing wicked problem issues, and then adopts hybrid structures to address this need.

The approach seeks to address wicked problem issues. Wicked problems do not respect academic disciplines, requiring a cross-disciplinary approach. Autonomous agency theory is adopted capable of structuring cross-disciplinary inquiry processes and formulating a hybrid inquiry paradigm. The paper sets up a narrative that delivers a structured essay resulting in a general theory of hybrid inquiry. This paradigm is explored in detail, considering how it can be applied to wicked problems.

The paradigm, which traditionally defines a field of study conceptualises and regulates approaches that enable inquiry into behavioural systems. Mono-disciplinary, they are not suitable for the resolution of issues that arise from cross-disciplinary wicked problems. To resolve this, a relational paradigm has been defined within which sits a cross-disciplinary hybrid inquiry system. A general theory of hybrid inquiry has been offered, with an appropriate illustration in ecosystem management. It is shown that agency theory can successfully embrace a relational paradigm.

To determine the limitations of this theory, there is a need to provide exemplars, which is currently premature. Another outcome is to centre on modes of practice in hybrid inquiry but there is insufficient space for this here.

This paper makes an original contribution by formulating a structured approach on the creation of a relational paradigm capable of supporting hybrid inquiry. It also adopts cross-disciplinary theory to make its case for a relational paradigm, recognising that wicked problems are cross-disciplinary. As part of the regulatory process it connects Rittel’s issue-based information system (IBIS) schema intended to resolve wicked problems issues and the Johari Window and explains how they would relate. A means is suggested for determining the degree of undecidability of wicked problems issues and hence that of the models that inquiry produces. This uses formative characteristics that define a modelling space. The paper also adopts Husserl’s concept or lifeworld, which acts as a channel for complex narrative theory through which regulative processes are enabled.

A multi-site, multi-source research methodology is suggested for scholars of corporate strategy in order to attain generalizability and statistical significance in reporting findings while not losing the nuances and understanding of each firm's environmental context.

Globalisation and liberalization of today's markets economy has posed new challenges to all manufacturing organizations, irrespective of their size and sector, for effective utilization of advanced manufacturing technologies (AMTs) for sustaining their competitiveness. The purpose of this paper is to provide a new insight into the use of hybrid methodology using analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach, which is a multi‐criteria decision‐making methodology for measuring the effective utilization of advanced manufacturing technologies.

A hybrid methodology using analytical hierarchy process and technique for order preference by similarity to ideal solution approach has been applied in this study. In this research work, seven factors such as top management support, resistance of employees, pay scale, training to employees, industry‐institute‐interaction, proper planning and team structure have been selected to determine the priority weights of attributes by using AHP. TOPSIS method is then employed to achieve the final ranking results. To benchmark the success possibility of AMTs utilization, AHP has been applied.

Top management support, resistance of employees and pay scale have been ranked as first, second and third important sub‐objectives for effective utilization of AMTs. While industry‐institute‐interaction, proper planning, training to employees and team structure have been placed at fourth, fifth, sixth and seventh positions for effective utilization of AMTs. It has been further noted that by using AHP, the successful utilization of AMTs can be found out.

The parameters selected for this study are applicable to the northern India manufacturing industry.

An attempt has been made to apply hybrid methodology approach using AHP and TOPSIS for effective utilization of AMTs. This is probably the first time that an attempt has been made to apply the hybrid methodology using AHP‐TOPSIS‐AHP for benchmarking the success possibility of utilization of AMTs in the northern Indian manufacturing industry.

With the development of research toward damage detection in structural elements, the use of artificial intelligent methods for crack detection plays a vital role in solving the crack-related problems. The purpose of this paper is to establish a methodology that can detect and analyze crack development in a beam structure subjected to transverse free vibration.

Hybrid intelligent systems have acquired their own distinction as a potential problem-solving methodology adopted by researchers and scientists. It can be applied in many areas like science, technology, business and commerce. There have been the efforts by researchers in the recent past to combine the individual artificial intelligent techniques in parallel to generate optimal solutions for the problems. So it is an innovative effort to develop a strong computationally intelligent hybrid system based on different combinations of available artificial intelligence (AI) techniques.

In the present research, an integration of different AI techniques has been tested for accuracy. Theoretical, numerical and experimental investigations have been carried out using a fix-hinge aluminum beam of specified dimension in the presence and absence of cracks. The paper also gives an insight into the comparison of relative crack locations and crack depths obtained from numerical and experimental results with that of the results of the hybrid intelligent model and found to be in good agreement.

The paper covers the work to verify the accuracy of hybrid controllers in a fix-hinge beam which is very rare to find in the available literature. To overcome the limitations of standalone AI techniques, a hybrid methodology has been adopted. The output results for crack location and crack depth have been compared with experimental results, and the deviation of results is found to be within the satisfactory limit.

The purpose of this paper is to propose a method for hybrid fire testing (HFT) which is unconditionally stable, ensures equilibrium and compatibility at the interface and captures the global behavior of the analyzed structure. HFT is a technique that allows assessing experimentally the fire performance of a structural element under real boundary conditions that capture the effect of the surrounding structure.

The paper starts with the analysis of the method used in the few previous HFT. Based on the analytical study of a simple one degree-of-freedom elastic system, it is shown that this previous method is fundamentally unstable in certain configurations that cannot be easily predicted in advance. Therefore, a new method is introduced to overcome the stability problem. The method is applied in a virtual hybrid test on a 2D reinforced concrete beam part of a moment-resisting frame.

It is shown through analytical developments and applicative examples that the stability of the method used in previous HFT depends on the stiffness ratio between the two substructures. The method is unstable when implemented in force control on a physical substructure that is less stiff than the surrounding structure. Conversely, the method is unstable when implemented in displacement control on a physical substructure stiffer than the remainder. In multi-degrees-of-freedom tests where the temperature will affect the stiffness of the elements, it is generally not possible to ensure continuous stability throughout the test using this former method. Therefore, a new method is proposed where the stability is not dependent on the stiffness ratio between the two substructures. Application of the new method in a virtual HFT proved to be stable, to ensure compatibility and equilibrium at the interface and to reproduce accurately the global structural behavior.

The paper provides a method to perform hybrid fire tests which overcomes the stability problem lying in the former method. The efficiency of the new method is demonstrated in a virtual HFT with three degrees-of-freedom at the interface, the next step being its implementation in a real (laboratory) hybrid test.

Service supplier selection is a multi-criteria decision-making (MCDM) problem assuming a strategic role for the competitiveness of high-tech manufacturing companies. Nevertheless, especially for service quality evaluation, there is little empirical evidence of the practical usefulness of MCDM methodologies. Aiming to cover this gap between theoretical approaches and empirical applications, the purpose of this paper is to propose a fuzzy extended analytic hierarchy process (FEAHP) approach for service supplier evaluation.

A hybrid approach which combines some of the strengths of the analytic hierarchy process (AHP) and of the fuzzy set theory is presented, as organized into five steps. A case study is used to evaluate the applicability in a real company context.

The usability of the approach is demonstrated in an aerospace company for solving the supplier selection problem of a business software whose applications are still in infancy: a Test Data Management System (TDMS). The illustrative application contains both “general” criteria to be used for other service supplier selection contexts as well as service-specific criteria related to software selection.

Even if the application regards the selection of a software supplier, the methodology can be generically extended to other services’ selection in complex manufacturing industries through the personalization of some criteria.

Implications can be derived both for business managers involved into the decision-making process and for suppliers identifying the most promising features of software quality.

The originality consists in the combination into a hybrid approach of the strong points of the AHP with the fuzzy set; the inclusion of multiple perspectives of decision criteria for service supplier selection, basically the “software product” and “supplier” ones; a real empirical application to test and demonstrate the efficacy and the practical utility of the proposed approach.

The purpose of this study is to examine state-of-the-art in hybrid-electric propulsion system modeling and suggest new methodologies for sizing such advanced concepts. Many entities are involved in the modelling and design of hybrid electric aircraft; however, the highly multidisciplinary nature of the problem means that most tools focus heavily on one discipline and over simplify others to keep the analysis reasonable in scope. Correctly sizing a hybrid-electric system requires knowledge of aircraft and engine performance along with a working knowledge of electrical and energy storage systems. The difficulty is compounded by the multi-timescale dynamic nature of the problem. Furthermore, the choice of energy management in a hybrid electric system presents multiple degrees of freedom, which means the aircraft sizing problem now becomes not just a root-finding exercise, but also a constrained optimization problem.

The hybrid electric vehicle sizing problem can be sub-divided into three areas: modelling methods/fidelity, energy management and optimization technique. The literature is reviewed to find desirable characteristics and features of each area. Subsequently, a new process for sizing a new hybrid electric aircraft is proposed by synthesizing techniques from model predictive control and detailed conceptual design modelling. Elements from model predictive control and concurrent optimization are combined to formulate a new structure for the optimization of the sizing and energy management of future aircraft.

While the example optimization formulation provided is specific to a hybrid electric concept, the proposed structure is general enough to be adapted to any vehicle concept which contains multiple degrees of control freedom that can be optimized continuously throughout a mission.

The proposed technique is novel in its application of model predictive control to the conceptual design phase.

The present paper describes the applicability of hybrid transfinite element modelling/analysis formulations for non‐linear heat conduction problems involving phase change. The methodology is based on application of transform approaches and classical Galerkin schemes with finite element formulations to maintain the modelling versatility and numerical features for computational analysis. In addition, in conjunction with the above, the effects due to latent heat are modelled using enthalpy formulations to enable a physically realistic approximation to be effectively dealt computationally for materials exhibiting phase change within a narrow band of temperatures. Pertinent details of the approach and computational scheme adapted are described in technical detail. Numerical test cases of comparative nature are presented to demonstrate the applicability of the proposed formulations for numerical modelling/analysis of non‐linear heat conduction problems involving phase change.