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Article
Publication date: 9 July 2021

Hosein Taghaddos, Mohammad Hosein Heydari and AmirHosein Asgari

This study aims to propose a hybrid simulation approach for site layout and material laydown planning in construction projects considering both the project’s continuous…

254

Abstract

Purpose

This study aims to propose a hybrid simulation approach for site layout and material laydown planning in construction projects considering both the project’s continuous and discrete state.

Design/methodology/approach

Efficient site layout planning (SLP) is a critical task at the early stages of the project to enhance constructability and reduce safety risks, construction duration and cost. In this paper, external and internal conditions affecting SLP gets identified. Then dynamic features of project conditions and project operations are analyzed by using a hybrid simulation approach combining continuous simulation (CS) and discrete event simulation (DES).

Findings

An efficient site layout plan regarding the project conditions results in cost efficiency. Instead of using DES or CS alone, this paper uses a hybrid simulation approach. Such a hybrid method leads to more accurate results that enable construction managers to make better decisions, such as material management variables. The proposed approach is implemented in a real construction project (i.e. earthmoving operation) to evaluate the hybrid simulation approach’s performance.

Practical implications

The proposed approach is implemented in a real construction project (i.e. earthmoving operation) to evaluate the performance of the hybrid simulation approach.

Originality/value

Although DES is used widely in construction simulation, it involves some limitations or inefficiencies. On the other hand, modeling resource interactions and capturing the construction project’s holistic nature with CS or system dynamics face some challenges. This study uses a hybrid DES and CS approach to enhance commercial construction projects’ SLP.

Article
Publication date: 15 February 2022

Danijela Ciric Lalic, Bojan Lalic, Milan Delić, Danijela Gracanin and Darko Stefanovic

This research aimed to explore whether different project management approaches (traditional, agile or hybrid) differentiate concerning their impact on project success…

2650

Abstract

Purpose

This research aimed to explore whether different project management approaches (traditional, agile or hybrid) differentiate concerning their impact on project success, taking project success as multidimensional phenomena. In addition to this, the authors wanted to explore if specific project characteristics moderate these effects.

Design/methodology/approach

The authors empirically addressed these on a sample of 227 project professionals worldwide. The exploratory factor analysis (EFA) of project success dimensions was done to validate these factors' constitution concerning their manifest variables. The K-means cluster method was used to distinguish respondents' profiles among agile, hybrid and traditional project management approaches. To test the significance among research groups, the research hypotheses were tested with ANOVA tests.

Findings

The authors evidenced that the agile approach has a more significant positive impact concerning the two out of five dimensions of project success, under analysis in this research (impact on the team and preparing for the future), over the traditional approach.

Practical implications

The research is relevant for project management practitioners to tailor the success-oriented project management approach and for academics to develop project management contingency theory.

Originality/value

The authors constructed a research framework to test the impact and effectiveness of different project management approaches (traditional, agile, hybrid) on the dimensions of project success in different contextual conditions (organization industry, project type, novelty, technology, complexity and pace). The paper's main contribution is to expand data on the impact of these approaches on project success and compare them with relevant results and findings of previous research.

Details

International Journal of Managing Projects in Business, vol. 15 no. 3
Type: Research Article
ISSN: 1753-8378

Keywords

Article
Publication date: 15 July 2019

Yong Li, Yanjun Huang and Xing Xu

Sensorless interior permanent magnet in-wheel motor (IPMIWM), as an exemplar of modular automation system, has attracted considerable interests in recent years. This paper…

118

Abstract

Purpose

Sensorless interior permanent magnet in-wheel motor (IPMIWM), as an exemplar of modular automation system, has attracted considerable interests in recent years. This paper aims to investigate a novel hybrid control approach for the sensorless IPMIWM from a cyber-physical systems (CPS) perspective.

Design/methodology/approach

The control approach is presented based on the hybrid dynamical theory. In the standstill-low (S-L) speed, the rotor position/speed signal is estimated by the method of the high frequency (HF) voltage signal injection. The least square support vector machine (LS-SVM) is used to acquire the rotor position/speed signal in medium-high (M-H) speed operation. Hybrid automata model of the IPMIWM is established due to its hybrid dynamic characteristics in wide speed range. A hybrid state observer (HSO), including a discrete state observer (DSO) and a continuous state observer (CSO), is designed for rotor position/speed estimation of the IPMIWM.

Findings

The hardware-in-the-loop testing based on dSPACE is carried out on the test bench. Experimental investigations demonstrate the hybrid control approach can not only identify the rotor position/speed signal with a certain load but also be able to reject the load disturbance. The reliability and the effectiveness of the proposed hybrid control approach were verified.

Originality/value

The proposed hybrid control approach for the sensorless IPMIWM promotes the deep combination and coordination of sensorless IPMIWM drive system. It also theoretically supports and extends the development of the hybrid control of the highly integrated modular automation system.

Article
Publication date: 5 January 2015

Saeed Moradi, Farnad Nasirzadeh and Farzaneh Golkhoo

The purpose of this research is to propose a hybrid simulation framework which can take into account both the continuous and operational variables affecting the…

Abstract

Purpose

The purpose of this research is to propose a hybrid simulation framework which can take into account both the continuous and operational variables affecting the performance of construction projects.

Design/methodology/approach

System dynamics (SD) simulation paradigm is implemented for the modelling of the complex inter-related structure of continuous variables and discrete event simulation (DES) is implemented for the modelling of operational influencing factors. A hybrid modelling framework is then proposed through combination of SD and DES to simulate the construction projects.

Findings

This paper discusses the deficiencies of two traditional simulation methods – SD and DES – for simulation of construction projects which can be compensated by implementing hybrid SD–DES model. Different types of basic hybrid structures and synchronisation methods of SD and DES models are introduced.

Practical implications

The proposed hybrid framework discussed in this research will be beneficial to modellers to simulate construction projects.

Originality/value

The paper introduces a theoretical framework for a hybrid continuous- discrete simulation approach which can take into account the dynamics of project environment arising from the complex inter-related structure of various continuous influencing factors as well as the construction operations. Different steps required to develop the hybrid SD–DES model and synchronisation of SD and DES simulation methods are illustrated.

Details

Construction Innovation, vol. 15 no. 1
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 27 November 2017

Serhat Peker, Altan Kocyigit and P. Erhan Eren

Predicting customers’ purchase behaviors is a challenging task. The literature has introduced the individual-level and the segment-based predictive modeling approaches for…

1027

Abstract

Purpose

Predicting customers’ purchase behaviors is a challenging task. The literature has introduced the individual-level and the segment-based predictive modeling approaches for this purpose. Each method has its own advantages and drawbacks, and performs in certain cases. The purpose of this paper is to propose a hybrid approach which predicts customers’ individual purchase behaviors and reduces the limitations of these two methods by combining the advantages of them.

Design/methodology/approach

The proposed hybrid approach is established based on individual-level and segment-based approaches and utilizes the historical transactional data and predictive algorithms to generate predictions. The effectiveness of the proposed approach is experimentally evaluated in the domain of supermarket shopping by using real-world data and using five popular machine learning classification algorithms including logistic regression, decision trees, support vector machines, neural networks and random forests.

Findings

A comparison of results shows that the proposed hybrid approach substantially outperforms the individual-level and the segment-based approaches in terms of prediction coverage while maintaining roughly comparable prediction accuracy to the individual-level method. Moreover, the experimental results demonstrate that logistic regression performs better than the other classifiers in predicting customer purchase behavior.

Practical implications

The study concludes that the proposed approach would be beneficial for enterprises in terms of designing customized services and one-to-one marketing strategies.

Originality/value

This study is the first attempt to adopt a hybrid approach combining individual-level and segment-based approaches to predict customers’ individual purchase behaviors.

Article
Publication date: 23 August 2022

Istijanto

This study aims to explore and compare the approach and avoidance factors in motivating students to study using three different learning methods: face-to-face learning…

Abstract

Purpose

This study aims to explore and compare the approach and avoidance factors in motivating students to study using three different learning methods: face-to-face learning, online learning and hybrid learning.

Design/methodology/approach

This research uses in-depth online interviews to gain insights from students. Purposive sampling was applied to recruit 33 informants from two private universities in Indonesia. The verbatim data were analyzed using a thematic content analysis to identify motivational factors.

Findings

This study revealed four motivational factors regarding the approach to face-to-face learning/avoidance of online learning and five motivational factors regarding the approach to online learning/avoidance of face-to-face learning. Most of the motivational factors (i.e. learning effectiveness, social interaction, campus life experiences, physical wellness, flexibility and technological learning) are also found in the approach to hybrid learning.

Research limitations/implications

The existing qualitative research suffers from generalizability, as does this study. Future research can investigate other contexts or use quantitative research to validate the findings.

Practical implications

By identifying the approach and avoidance motivational factors, higher education institutions can enhance the approach (positive) factors and minimize or eliminate the avoidance (negative) factors that motivate their students to study using different learning methods.

Originality/value

This research complements the existing literature using new perspectives, namely, the approach and avoidance factors that motivate students to study through face-to-face learning, online learning and hybrid learning post-COVID-19.

Details

Quality Assurance in Education, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0968-4883

Keywords

Article
Publication date: 15 July 2021

Kathiresh Mayilsamy, Maideen Abdhulkader Jeylani A,, Mahaboob Subahani Akbarali and Haripranesh Sathiyanarayanan

The purpose of this paper is to develop a hybrid algorithm, which is a blend of auto-regressive integral moving average (ARIMA) and multilayer perceptron (MLP) for…

Abstract

Purpose

The purpose of this paper is to develop a hybrid algorithm, which is a blend of auto-regressive integral moving average (ARIMA) and multilayer perceptron (MLP) for addressing the non-linearity of the load time series.

Design/methodology/approach

Short-term load forecasting is a complex process as the nature of the load-time series data is highly nonlinear. So, only ARIMA-based load forecasting will not provide accurate results. Hence, ARIMA is combined with MLP, a deep learning approach that models the resultant data from ARIMA and processes them further for Modelling the non-linearity.

Findings

The proposed hybrid approach detects the residuals of the ARIMA, a linear statistical technique and models these residuals with MLP neural network. As the non-linearity of the load time series is approximated in this error modeling process, the proposed approach produces accurate forecasting results of the hourly loads.

Originality/value

The effectiveness of the proposed approach is tested in the laboratory with the real load data of a metropolitan city from South India. The performance of the proposed hybrid approach is compared with the conventional methods based on the metrics such as mean absolute percentage error and root mean square error. The comparative results show that the proposed prediction strategy outperforms the other hybrid methods in terms of accuracy.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 40 no. 3
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 16 January 2017

Kathryn Davies, Dermott J. McMeel and Suzanne Wilkinson

Although the potential of Building Information Modelling (BIM) to generate process and performance improvement in the construction industry has been widely documented…

1014

Abstract

Purpose

Although the potential of Building Information Modelling (BIM) to generate process and performance improvement in the construction industry has been widely documented, very few projects operate in a wholly BIM environment. The purpose of this paper is to explore the factors that lead to hybrid practice in BIM across disciplines or project stages, and accommodations that must be reached within BIM project frameworks to allow for it.

Design/methodology/approach

In-depth semi-structured interviews were carried out with 38 BIM specialists from Australia and New Zealand, representing a variety of construction industry disciplines and roles. Data on current practice and experiences in BIM were analysed using a thematic approach within a qualitative framework.

Findings

Hybrid BIM practice is shown to be a common experience for practitioners in New Zealand and Australia. It is presented as a valid model of BIM adoption; both as a development stage in the process towards more complete BIM implementation, and also as an adoption model in its own right.

Research limitations/implications

The paper is based on data from New Zealand and Australia, which are currently developing BIM markets. Although surveys have demonstrated many similarities in BIM adoption processes internationally, results may be less applicable to more mature markets.

Practical implications

The paper suggests that instead of regarding hybrid BIM negatively as an unsuccessful implementation, companies should seek to identify and manage the causes and effects of hybridisation in order to improve project outcomes.

Originality/value

This paper addresses the management of transitional stages of BIM implementation, which is often overlooked in research.

Details

Engineering, Construction and Architectural Management, vol. 24 no. 1
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 3 August 2022

Dominik Quillet, Vincent Boulanger, David Rancourt, Richard Freer and Pierre Bertrand

Parallel hybrid electric (HE) propulsion retrofit is a promising alternative to reduce fuel burn of aircraft operating on short regional flights. However, if the batteries…

Abstract

Purpose

Parallel hybrid electric (HE) propulsion retrofit is a promising alternative to reduce fuel burn of aircraft operating on short regional flights. However, if the batteries are depleted at the end of the mission, the hybrid powertrain designs with downsized gas turbines (GTs) and additional electric motors might not meet the one-engine inoperative (OEI) missed approach climb performance required by the certification. Alternatively, hybrid designs using the original full-size GT can perform one engine climb without electric assistance. This paper aims to evaluate the impact of overshoot climb requirements on powertrain design and performance comparing the two design approaches.

Design/methodology/approach

An aircraft-level parametric mission analysis model is used to evaluate aircraft performance combined with an optimization framework including multiple constraints. An indirect approach using metamodels is used to optimize powertrain sizing and operation strategy.

Findings

Considering OEI climb requirements, no benefits were found using a design with downsized GTs. Equivalent fuel burns were found for hybrid designs that keep the original size GTs, but do not require electric energy for the OEI overshoot at the end of the mission. Then, it is recommended to size the GT to maintain the emergency climb capabilities with no electric assistance to ensure power availability regardless of remaining battery energy.

Originality/value

This work introduces a new perspective on parallel HE sizing with consideration for the dependency of power capability at aircraft level on the electric energy availability in case of critical mission scenarios such as overshoot climb at the end of the mission.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 2 November 2022

Feng Bai and Yi Wang

The purpose of this paper is to establish an intelligent framework to generate the data representatives in snapshot simulation in order to construct the online…

Abstract

Purpose

The purpose of this paper is to establish an intelligent framework to generate the data representatives in snapshot simulation in order to construct the online reduced-order model based on the generated data information. It could greatly reduce the computational time in snapshot simulation and accelerate the computational efficiency in the real-time computation of reduced-order modeling.

Design/methodology/approach

The snapshot simulation, which generates the data to construct reduced-order models (ROMs), usually is computationally demanding. In order to accelerate the snapshot generation, this paper presents a discrete element interpolaiton method (DEIM)-embedded hybrid simulation approach, in which the entire snapshot simulation is partitioned into multiple intervals of equal length. One of the three models: the full order model (FOM), local ROM, or local ROM-DEIM which represents a hierarchy of model approximations, fidelities and computational costs, will be adopted in each interval.

Findings

The outcome of the proposed snapshot simulation is an efficient ROM-DEIM applicable to various online simulations. Compared with the traditional FOM and the hybrid method without DEIM, the proposed method is able to accelerate the snapshot simulation by 54.4%–63.91% and 10.5%–27.85%, respectively. In the online simulation, ROM-DEIM only takes 4.81%–8.56% of the computational time of FOM, while preserving excellent accuracy (with relative error <1%).

Originality/value

1. A DEIM-embedded hybrid snapshot simulation methodology is proposed to accelerate snapshot data generation and reduced-order model (ROM)-DEIM development. 2. The simulation alternates among FOM, ROM and ROM-DEIM to adaptively generate snapshot data of salient subspace representation while minimizing computational load. 3. The DEIM-embedded hybrid snapshot approach demonstrates excellent accuracy (<1% error) and computational efficiency in both online snapshot simulation and online ROM-DEIM verification simulation.

Details

Engineering Computations, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-4401

Keywords

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