O.O. UGWU and J.H.M. TAH
Resource selection/optimization problems are often characterized by two related problems: numerical function and combinatorial optimization. Although techniques ranging from…
Abstract
Resource selection/optimization problems are often characterized by two related problems: numerical function and combinatorial optimization. Although techniques ranging from classical mathematical programming to knowledge‐based expert systems (KBESs) have been applied to solve the function optimization problem, there still exists the need for improved solution techniques in solving the combinatorial optimization. This paper reports an exploratory work that investigates the integration of genetic algorithms (GAs) with organizational databases to solve the combinatorial problem in resource optimization and management. The solution strategy involved using two levels of knowledge (declarative and procedural) to address the problems of numerical function, and combinatorial optimization of resources. The research shows that GAs can be effectively integrated into the evolving decision support systems (DSSs) for resource optimization and management, and that integrating a hybrid GA that incorporates resource economic and productivity factors, would facilitate the development of a more robust DSS. This helps to overcome the major limitations of current optimization techniques such as linear programming and monolithic techniques such as the KBES. The results also highlighted that GA exhibits the chaotic characteristics that are often observed in other complex non‐linear dynamic systems. The empirical results are discussed, and some recommendations given on how to achieve improved results in adapting GAs for decision support in the architecture, engineering and construction (AEC) sector.
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J.H.M. TAH, V. CARR and R. HOWES
Previous approaches to decision support for project planning using rule‐based expert systems techniques have failed to make an impact in practice. This is primarily because of the…
Abstract
Previous approaches to decision support for project planning using rule‐based expert systems techniques have failed to make an impact in practice. This is primarily because of the complexity and large‐scale nature of construction information, and problems with expert systems including: knowledge acquisition; rule‐based knowledge representation; information storage (or memory); learning; and robustness. Case‐based reasoning is one area of current research which may hold the key to overcoming a number of these problems. In the present paper, previous related case‐based reasoning work is examined. The key factors which influence the formulation of construction project plans are identified. This knowledge is used to develop a conceptual framework within which previous planning experiences can be captured and reused in new situations as a means of providing system decision support in construction planning and control. A prototype system, CBRidge, developed to test and demonstrate the concepts within the framework is presented. The results are very encouraging and provide a sound basis for the further development of case‐based reasoning for construction planning in practice.
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J.H.M. TAH and V. CARR
The construction industry is greatly plagued by risk; too often, this risk is not dealt with adequately, resulting in poor project performance. Communication of construction…
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The construction industry is greatly plagued by risk; too often, this risk is not dealt with adequately, resulting in poor project performance. Communication of construction project risks in practice is poor, incomplete and inconsistent, both throughout the supply chain and through the project lifecycle. Part of the problem is the lack of a formalized approach to the project risk management process. Recently, attempts have been made to overcome this and this paper uses these attempts as a foundation for building a better approach to construction risk management. Underlying this approach is the development of a common language for describing risks and remedial actions. This is grounded in a taxonomy of risk based on a hierarchical risk breakdown structure. In addition, to facilitate the production of a working risk management system, a number of models have been developed using unified modelling language (UML) and IDEFO. Finally, the use of the system has been tested via a working software prototype. This prototype is being used as a basis for discussion with practitioners with regard to the practical requirements of the approach for further development.
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E.N. WIRBA, J.H.M. TAH and R. HOWES
Risk analysis has come to be seen as a quantitative process in which risks are measured by the use of probabilities. However, since every new project is essentially unique with no…
Abstract
Risk analysis has come to be seen as a quantitative process in which risks are measured by the use of probabilities. However, since every new project is essentially unique with no previous data on it, decisions taken as to the nature of the risks are highly subjective and the actions that may be carried out to mitigate the effects of these risks are not clear‐cut; a non‐numerical approach can, therefore, be more useful. The risk management approach detailed here identifies the risks, checks for dependence amongst risks, and assesses the likelihood of occurrence of each risk by using linguistic variables through the medium of fuzzy sets. The use of linguistic variables is a departure from conventional risk analysis methods that rely rather heavily on statistical analysis to quantify the effects of risks on projects. The entire risk management process is explained, and a case study is carried out to demonstrate the use of the ideas treated. The case study concentrates on the activities of the substructure in a multi‐storey building project. The ten largest risks are identified, and dependence among them is assessed through fuzzy set calculations. The assessment of risk dependencies brings about a reduction in the total number of risks analysed, as highly dependent risks are treated together, and the use of linguistic variables brings about a non‐numeric approach to risk analysis with which project managers can be comfortable. The risk management process, through the use of fuzzy sets, is better able to handle project management knowledge on risk analysis which is highly subjective, and varies from project to project.
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Temidayo Oluwasola Osunsanmi, Clinton Ohis Aigbavboa, Wellington Didibhuku Thwala and Ayodeji Emmanuel Oke
The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The…
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The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The analysis from the literature revealed that the implementation of SCM in the construction industry enhances the industry's value in terms of cost-saving, time savings, material management, risk management and others. The construction supply chain (CSC) can be managed using the pull or push system. This chapter also discusses the origin and proliferation of SCM into the construction industry. The chapter revealed that the concept of SCM has passed through five different eras: the creation era, the use of ERP, globalisation stage, specialisation stage and electronic stage. The findings from the literature revealed that we are presently in the fourth industrial revolution (4IR) era. At this stage, the SCM witnesses the adoption of technologies and principles driven by the 4IR. This chapter also revealed that the practice of SCM in the construction industry is centred around integration, collaboration, communication and the structure of the supply chain (SC). The forms and challenges hindering the adoption of these practices were also discussed extensively in this chapter.
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Temidayo Oluwasola Osunsanmi, Clinton Ohis Aigbavboa, Wellington Didibhuku Thwala and Ayodeji Emmanuel Oke
The model and existing practice of the construction supply chain (CSC) in the United Kingdom (UK) and Australia was presented in this chapter. The policies and reports that…
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The model and existing practice of the construction supply chain (CSC) in the United Kingdom (UK) and Australia was presented in this chapter. The policies and reports that support the practice of the CSC were examined in both countries. It was discovered from the review of literature that the UK has a more detailed report targeted at improving the CSC than Australia. However, both countries have a common factor affecting their CSC which originates from fragmentation experienced within their supply chain. Construction stakeholders in the UK and Australia believe that collaboration and integration are vital components for improving performance. The majority of the contractors in both countries embrace collaborative working for the sole purpose of risk sharing, access to innovation and response to market efficiency. However, most of the models developed for managing the CSC in the UK are built around building information modelling (BIM). Also, the reviewed studies show that supply chain management practice will be effective following the following principle: shared objectives, trust, reduction in a blame culture, joint working, enhanced communication and information-sharing. Finally, the UK has a more established framework and more CSC models compared to Australia.
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Temidayo Oluwasola Osunsanmi, Clinton Ohis Aigbavboa, Wellington Didibhuku Thwala and Ayodeji Emmanuel Oke
This chapter aimed to uncover the gaps in the existing construction supply chain management (CSCM) models. Organisational culture and the fourth industrial revolution (4IR…
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This chapter aimed to uncover the gaps in the existing construction supply chain management (CSCM) models. Organisational culture and the fourth industrial revolution (4IR) components are the two gaps that were identified through reviewing existing CSCM models. The 4IR is driven by three components which are smart management, virtualisation and cyber-physical system. It was proposed in this chapter that the practice of CSCM should be in tandem with the components of 4IR. This chapter recommended that for the effective practice of the construction supply chain (CSC) in the 4IR era, construction stakeholders should adopt an innovative and collaborative organisational culture. The organisational culture adopted by a construction firm performs a crucial role in encouraging construction stakeholders in adopting 4IR components for CSCM. Each of the 4IR components is driven by technologies like autonomous robots, building information modelling (BIM), radio frequency identification (RFID), the internet of things (IoT) and others. Among all the technologies, it was discovered that RFID and BIM had gained prominence in most CSC literature. The chapter recommended that blockchain, digital twins and the cyber-physical system are the next trending technology for CSCM.
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NASHWAN N. DAWOOD and WILLIAM BATES
The heavy civil engineering industry (railways, sewage treatment, chemical and pharmaceutical facilities, oil and gas facilities, etc.) is one of the major contributors to the…
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The heavy civil engineering industry (railways, sewage treatment, chemical and pharmaceutical facilities, oil and gas facilities, etc.) is one of the major contributors to the British economy and generally involves a high level of investment. Clients in this industry are demanding accurate cost estimate, proper analysis of out‐turn cost and cost escalation and a high quality risk analysis throughout the construction processes. Current practice in the industry has suggested that there is a lack of structured methodologies and systematic cost escalation approach to achieve an appropriate cost analysis at the outset of projects and throughout the construction processes. In this context the prime objective of this research work is to develop a structured cost escalation methodology for improving estimating management and control in the heavy engineering industry construction processes. The methodology is composed of a forecasting model to predict cost indices of major items in industry and a risk knowledge base model for identifying and quantifying causes of cost escalations. This paper, as part of the research, reviews and discusses a knowledge‐based model for applying a cost escalation factor. The cost escalation factor is made up of market variation, a risk element and a component for bias. A knowledge elicitation strategy was employed to obtain the required knowledge for the model. The strategy included questionnaires, interviews and workshops and deliverables came in the form of influences and their effect on project cost escalation. From these deliverables, the concepts of a decision support model and system specification for applying cost escalation to base estimates is proposed.
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Temidayo Oluwasola Osunsanmi, Clinton Ohis Aigbavboa, Wellington Didibhuku Thwala and Ayodeji Emmanuel Oke
This chapter focused on presenting the result of the Delphi study from the questionnaire distributed to the experts. The Delphi technique was used for modelling the construction…
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This chapter focused on presenting the result of the Delphi study from the questionnaire distributed to the experts. The Delphi technique was used for modelling the construction supply chain management (CSCM) practice in the fourth industrial revolution (4IR) era. The technique was also used to predict the supply chain management's (SCM) possible trends in the construction industry. A total of 15 experts were selected for this study based on their working experience. The Delphi study also validated the gaps (organisational culture and 4IR component) identified from the existing CSCM model. The findings from the Delphi study revealed that organisational culture has a significant impact on the practice of CSCM in the 4IR era. Regarding adopting the 4IR component for the CSCM in Nigeria, the Delphi study revealed that smart management and virtualisation are the most adopted. Unfortunately, the cyber-physical system, the heartbeat of the 4IR, is yet to be fully implemented for CSCM practice in the Nigerian construction industry.
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One of the major reasons for ineffective project delivery in the Nigerian construction industry is the improper assessment of risk factors. As a result, the industry continues to…
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One of the major reasons for ineffective project delivery in the Nigerian construction industry is the improper assessment of risk factors. As a result, the industry continues to suffer poor performance with many projects failing to meet time and cost targets. This paper identifies the risk factors inherent in different building procurement methods and assesses their perceived relative importance with a view to evaluating their impact on project cost. The paper reports on a study carried out through a questionnaire survey of professionals within the construction industry in order to asses the relative importance placed on risk factors. Responses from the survey were analysed using relative importance index for the purpose of evaluating the impact of risk on projects cost. Data were collected on selected completed projects and analysed using frequencies, mean values and relative important index. The main risk factors identified are finance and political influence. A model was developed by relating the variation between the initial contract estimate and the actual project cost to the risk variables. From the analysis, the percentages of projects cost overrun due to the impact of risk were established for each procurement method investigated. The paper recommends that contingency additions should be based on the procurement method used.