In projects with repeating activities (such as multistory buildings, highways, or pipelines consisting of reiterating identical or similar units) and in which the activity unit production rates are characterized by uncertainty or imprecision, fuzzy set theory and the well-established repetitive scheduling method (RSM) can be combined to ensure uninterrupted usage of resources between similar activities in different units. The reason for this approach is that in practice the application of RSM may be hindered by several considerations, for example, repetitive units may be slightly different from each other, the performance of construction crews may vary, and there may be complex resource matching and sharing between activities and work sites. The proposed methodology is termed fuzzy repetitive scheduling method (F-RSM), and it requires a generalization of RSM in which schedules are represented by two- or three-dimensional graphs and whereby the concepts of a control segment and the controlling sequence are...

Cost‐benefit analysis (CBA) is very useful when appraising engineering projects and examining their long‐term financial and social sustainability. However, the inherent uncertainty in the estimation of completion time, final costs, and the realization of benefits often act as an impediment to its application. Since the emergence of fuzzy set theory, there have been significant developments in uncertainty modelling in project evaluation and investment analysis, primarily in the area of formulating a fuzzy version of CBA. In this context, in studying the key indicators of CBA, whereas fuzzy net present value (fNPV) has been investigated quite extensively, there are significant issues in the calculation of fuzzy internal rate of return (fIRR) that have not been addressed. Hence, this paper presents a new conceptual model for studying and calculating fNPV and fIRR. Three‐dimensional fNPV and fIRR graphs are introduced as a means of visualizing uncertainty. A new approach is presented for the precise calculation of fIRR. To facilitate practical application, a computerization process is also presented. Additionally, the proposed methodology is exemplified in a sample motorway project whereby its advantages over traditional stochastic uncertainty modelling techniques such as Monte Carlo analysis are discussed. Overall, it is concluded that the new approach is very promising for modelling uncertainty during project evaluation for both project managers and project stakeholders.

Conceptual pre-estimation of road tunnel costs is a vital yet challenging process during feasibility studies due to the prevailing underground uncertainties and risks. Most existing cost estimation approaches are deterministic, probabilistic methods are limited to a single cost examination. This paper introduces a probabilistic model for pre-estimating road tunnels life-cycle costs. It aims to capture their inherent uncertainty holistically, thus enabling more reliable decision-making at a project’s early stages. The proposed model is developed in three steps: multiple regression analysis, fitting distribution, and Monte-Carlo simulation. The first step unveils the correlations between independent and dependent variables, while the other two steps return the probabilistic descriptions of cost drivers and life-cycle costs. Civil engineering, electromechanical works costs, energy consumption, and operation & maintenance costs are determined as the model’s output variables. A real-world database of 32 dual-bore road tunnels with a total length of 55 km is used to develop probability distributions within reasonable confidence intervals and a sensitivity analysis was performed utilizing tornado charts. The results can assist public authorities and managers in estimating the probability of a specific life-cycle cost and making appropriate decisions in accordance with their risk tolerance.

The rational selection of transport infrastructure projects to implement is critical in ensuring the best allocation of available funding. To this purpose, Cost Benefit Analysis has been employed by national and regional authorities in order to maximize economic and social benefits, and by the European Commission to ensure the appropriate level of grants. Furthermore, a risk assessment is conducted, which is based primarily on a sensitivity analysis and/or a stochastic risk analysis. However, due to the high degree of uncertainty in the current economic environment, there are several shortcomings in this approach. Thus, an alternative application is proposed that models the uncertainty of critical variables with the aid of Fuzzy Set Theory. The application is exemplified in a sample transport project whereby its advantages over traditional approaches are discussed. It is concluded that fuzzy Cost Benefit Analysis is a promising tool for modeling uncertainty

There is a global tendency towards implementing centralized project monitoring with the use of advanced information systems in large projects. This trend is mandated by issues such as the geographical dispersion of projects, the number of contractors and the total amount of works. In this respect, the integrated information system that has been utilized to monitor the construction works of the Egnatia Motorway project in Greece is presented. Reference is made to the software, hardware, information technology architecture, quality procedures and personnel training for the successful implementation of the system. Special mention is made to the data structures that are utilised (enterprise project structure, organizational breakdown structure, resource breakdown structure, and work breakdown structure). In addition, comments are made from the experiences drawn from the implementation of the system. Overall, it is concluded that the integrated system constitutes a central focal point for corporate scheduling and cost control.