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The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).

The model contains a cost objective function, generalized precedence relationship constraints, activity duration and start time constraints, lag/lead time constraints, execution mode (EM) constraints, project duration constraints, working time unit assignment constraints and resource constraints. The mixed-integer nonlinear programming (MINLP) superstructure of discrete solutions covers time–cost–resource options related to various EMs for project activities as well as variants for production process implementation.

The proposed model provides the exact optimal output data for project management, such as network diagrams, Gantt charts, histograms and S-curves. In contrast to classic scheduling approaches, here the optimal project structure is obtained as a model-endogenous decision. The project planner is thus enabled to achieve optimization of the production process simultaneously with resource-constrained scheduling of activities in discrete time units and at a minimum total cost.

A set of application examples are addressed on an actual construction project to display the advantages of proposed model.

The unique value this paper contributes to the body of knowledge reflects through the proposed MINLP model, which is capable of performing the exact cost optimization of production process (where presence and number of activities including their mutual relations are dealt as feasible alternatives, meaning not as fixed parameters) simultaneously with the associated resource-constrained project scheduling, whereby that is achieved within a uniform procedure.

Safety planning in construction project management is separated from other planning functions, such as scheduling. This separation creates difficulties for safety engineers to analyse what, when, why and where safety measures are needed for preventing accidents. Another problem occurs due to the conventional practice of representing project designs using two‐dimensional (2D) drawings. In this practice, an engineer has to convert the 2D drawings into three‐dimensional (3D) mental pictures which is a tedious task. Since this conversion is already difficult, combining these 2D drawings with safety plans increases the difficulty. In order to address the problems, 4DCAD‐Safety is proposed. This paper discusses the design and development of 4DCAD‐Safety application and testing its usefulness in terms of assisting users in analysing what, when, where and why safety measures are needed.

Sets out to examine earned value management (EVM), a project management technique that relates resource planning to schedules, technical costs and schedule requirements.

Provides an example of how EVM can be implemented in a data warehouse project and how it can be used as a tool to diagnose and solve problems.

EVM is based on the belief that the value of the project increases as tasks are completed and therefore the earned value of a project is a measure of the real progress of that project.

Offers a significant analysis of EVM, its benefits and pitfalls.

Successful performance and execution of construction projects depend highly on a good project control system capable of tracking and reporting project status on a desired time interval. The purpose of this paper is to propose such a control system by integrating spreadsheet and Visual Basic for Application to produce a customized tracking system for Pipeline Relocation Programs under Engineering, Procurement and Construction Management (EPCM) contracts.

The project status reporting system (PSRS) proposed here was developed to produce a single page summary report that would include scope information, financial status, descriptive status updates and top-level task schedules. This information is retrieved from various sources and transformed further utilizing specific formulas and algorithm needed to compute the budget and schedule status of the pipe relocation project. A practical case study is used to demonstrate its unique application.

The system has successfully integrated project finance and schedule information into a central control hub. Financial and schedule performance of a project is tracked and monitored by the PSRS automatically.

The proposed system utilizes the powerful computing capability of MS Excel and the user-friendly VBA programming tool to customize the reporting needs of a project and program environment. The proposed system, whose functionality has been validated by the intended users, tries to achieve a balance between simplicity, accuracy and effectiveness for the flow of information at a much lower cost compared to the other readily available project control software.

The purpose of this paper is to present a detailed case study on the methods and organisational structure used for controlling the time schedule for a large and complex project. The paper discusses the use of “project controlling”, a term used to describe project control by a third-party organisation.

The researchers used action research to collect data for the case study. A member of the research team was a “participant-observer” on the project on a day-to-day basis for a period of 18 months collecting and analysing data which were subsequently analysed by a mixed methods approach.

The use of a “Project Controlling Unit” operated by an independent adviser organisation has significant advantages over traditional methods. It can provide timely, consolidated, independent guidance to the client and assistance to other participating organisations.

The research has confirmed the effectiveness of the method on the project under study.

The findings provide guidance for enhanced project control on large complex infrastructural projects that will be of interest to other researchers, other clients and other construction organisations both within China and internationally.

Organisations that seek to develop Project Controlling Units to implement the methods described in this paper will need to review their recruitment and training strategies to ensure that appropriate and experienced staffs are engaged.

The paper extends the knowledge relating to “project controlling” method. The findings provide additional insights to progress reporting and the management of construction production on HOPSCA and other large infrastructural projects.

The purpose of this study is to optimize short‐term maintenance scheduling of utility systems satisfying network constraints.

A mathematical programming model with network constraints is presented.

There are some cases in which the maintenance of a certain unit affects the operations of non‐maintenance units. The schedule should be evaluated by labor cost, material cost and opportunity costs. However, most utility systems contain dual‐directional flows, making the interdependency of the units an unstable element. In such systems, the dependency between one unit and the other should be adjusted depending on the conditions.

Power, steam and water are distributed by utility systems. Unit maintenance affects the operation of non‐maintenance units within the networks. Effective short‐term maintenance scheduling of utility systems must work within these network constraints. Unlike conventional scheduling methods, the excessive concentration of maintenance tasks should be controlled to reduce supply losses. A mixed integer linear programming model was utilized for identifying the solution of the problem. The present model can be applied to various utility systems.

The model can address alternative flows to reflect current conditions. Binary variables are applied to preserve the consistency of flow balances. The logic tree analysis expressed the current flow balances using linear constraints. The effectiveness of the model was supported by case examples.

This research presents a framework that allows project managers to predict the next critical paths (CP(s)) and to take extra care when planning and executing those activities that have the potential to cause changes in a project's current CP(s).

The method presented here is based on an assessment of each activity's contribution to the overall schedule variance, which involves assigning a probability distribution function to each activity duration in the project. A sensitivity analysis is also carried out, which forms the basis of identifying which activity most affects the project completion date and therefore will have the greatest effect in changing the CP.

The authors’ analysis reveals that the most appropriate probability density function (PDF) for the targeted project is the normal distribution. However, the aim of this work is not to determine the most suitable distribution for each activity but rather to study the effect of the activity distribution type on the CP prediction. The results show that the selection of the appropriate probability distribution is very important, since it can impact the CP prediction and estimated project completion date.

This research work proposes a delay analysis scheme which can help the project manager to predict the next CP and to improve performance by identifying which activity is the bottleneck. On the other hand, the simplicity arises from the fact that this method does not require any expensive machines or software to generate results.

Construction activities conducted in urban areas are often a source of significant noise disturbances, which cause psychological and health issues for residents as well as long-term auditory impairments for construction workers. The limited effectiveness of passive noise control measures due to the close proximity of the construction site to surrounding neighborhoods often results in complaints and eventually lawsuits. These can then lead to delays and cost overruns for the construction projects.

The paper proposes a novel approach to integrating construction noise as an additional dimension into scheduling construction works. To achieve this, a building information model, including the three-dimensional construction site layout object geometry, resource allocation and schedule information, is utilized. The developed method explores further project data that are typically available, such as the assigned equipment to a task, its precise location, and the estimated duration of noisy tasks. This results in a noise prediction model by using noise mapping techniques and suggesting less noisy alternative ways of construction. Finally, noise data obtained from sensors in a case study contribute real values for validating the proposed approach, which can be used later to suggest solutions for noise mitigation.

The results of this study indicate that the proposed approach can accurately predict construction noise given a few available parameters from digital project planning and sensors installed on a construction site. Proactively integrating construction noise control measures into the planning process has benefits for both residents and construction managers, as it reduces construction noise-related disturbances, prevents unexpected legal issues and ensures the health and well-being of the workforce.

While previous research has concentrated on real-time data collection using sensors, a more effective solution would also involve addressing and mitigating construction noise during the pre-construction work planning phase.

The purpose of this paper is to develop a building information modelling (BIM)-based multi-objective optimization (MOO) framework for volumetric analysis of buildings during early design stages. The objective is to optimize volumetric spaces (3D) instead of 2D spaces to enhance space utilization, thermal comfort, constructability and rental value of buildings

The integration of two fundamental concepts – BIM and MOO, forms the basis of proposed framework. In the early design phases of a project, BIM is used to generate precise building volume data. The non-sorting genetic algorithm-II, a MOO algorithm, is then used to optimize extracted volume data from 3D BIM models, considering four objectives: space utilization, thermal comfort, rental value and construction cost. The framework is implemented in context of a school of architecture building project.

The findings of case study demonstrate significant improvements resulting from MOO of building volumes. Space utilization increased by 30%, while thermal comfort improved by 20%, and construction costs were reduced by 10%. Furthermore, rental value of the case study building increased by 33%.

The proposed framework offers practical implications by enabling project teams to generate optimal building floor layouts during early design stages, thereby avoiding late costly changes during construction phase of project.

The integration of BIM and MOO in this study provides a unique approach to optimize building volumes considering multiple factors during early design stages of a project

Most projects are facing delays, and accelerating the pace of project progress is a necessity. Project managers are responsible for completing the project on time with minimum cost and with maximum quality. This study provides a trade-off between time, cost, and quality objectives to optimize project scheduling.

The current paper presents a new resource-constrained multi-mode time–cost–quality trade-off project scheduling model with lags under finish-to-start relations. To be more realistic, crashing and overlapping techniques are utilized. To handle uncertainty, which is a source of project complexity, interval-valued fuzzy sets are adopted on several parameters. In addition, a new hybrid solution approach is developed to cope with interval-valued fuzzy mathematical model that is based on different alpha-levels and compensatory methods. To find the compatible solution among conflicting objectives, an arithmetical average method is provided as a compensatory approach.

The interval-valued fuzzy sets approach proposed in this paper is denoted to be scalable, efficient, generalizable and practical in project environments. The results demonstrated that the crashing and overlapping techniques improve time–cost–quality trade-off project scheduling model. Also, interval-valued fuzzy sets can properly manage expressions of the uncertainty of projects which are realistic and practical. The proposed mathematical model is validated by solving a medium-sized dataset an adopted case study. In addition, with a sensitivity analysis approach, the solutions are compared and the model performance is confirmed.

This paper introduces a new continuous-based, resource-constrained, and multi-mode model with crashing and overlapping techniques simultaneously. In addition, a new hybrid compensatory solution approach is extended based on different alpha-levels to handle interval-valued fuzzy multi-objective mathematical model of project scheduling with influential uncertain parameters.