A dynamic crashing method for project management using simulation-based optimization

Kühl,; Tolentino-Pena,

doi:10.1109/wsc.2008.4736344

Cited by 13 publications

(7 citation statements)

References 7 publications

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“…There are no specific ways to ignore uncertainties except by reducing, managing and tackling the problems from detailed investigation, such as diagnose and analyse the causes and effects. Frequently, the project will be planned, scheduled and organized using a Critical Path Method (CPM) [14,15] and Program Evaluation Review Technique (PERT) [16,17]. The project is planned with a simple computer software such as Primawera or Microsoft office package software such as Visio, Project and Excel [18].…”

Section: Multi Project Constrcution Environmentmentioning

confidence: 99%

The development of simulation logic model that dealing with uncertainty for piping construction industry

Baharum

Mahdin

Rahman

2020

IJEECS

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<p>Basically, multi processes and activities involve in the piping construction (PC) projects needs to be followed before the project is handed over to the customer or client, called multi-project construction environment (MPCE). In PC, the MPCEs exist where more than one project is managed simultaneously within an organization become as a common phenomenon faced by managers that highly possible to face with uncertainty issues, lead to project completion late delivery (PCLD). Dealing with uncertainty in MPCE is a common, though managing uncertainty in PC become more complicated rather that others industry. Therefore, the objective of this paper is to develop the simulation logic model to deal with the uncertainty for PC projects that focused on environmental issues (EI). This result will be proceed for uncertainty model development in the next phase of this research. The simulation logic model development began with qualitative data collection towards the case study, to get all the activities throughout the water supply company. Then, the business model is developed with 14 activities before integrated with the uncertainty factors in EI. The integration of business model and uncertainty factors generated the simulation logic model as main contribution. Once the uncertainty model completely developed, it will provide a medium for PC that confront with MPCE to monitor the uncertainties and prepared to encounter any matters in future. Therefore, it is important to pursue in providing the PC company to all inclusive-model, and helping them in managing and tackling the uncertainty, especially for EI.</p>

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Section: Multi Project Constrcution Environmentmentioning

confidence: 99%

The development of simulation logic model that dealing with uncertainty for piping construction industry

Baharum

Mahdin

Rahman

2020

IJEECS

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“…Bashir and Thomson presented a thorough quantitative estimation approach which can offer initial along with updated project estimates from manageability or feasibility study until project completion [33]. A dynamic simulation-based crashing methodology was introduced to assess project networks and determine the optimum crashing configuration that reduces the average project cost to a minimum level because of delayed penalties and crashing costs [34]. Their dynamic method allows us to assess the project network to design a crashing strategy at the very onset of the project execution and also during the time that the project is being performed.…”

Section: Simulation Project Techniquesmentioning

confidence: 99%

Designing a Framework to Improve Time Series Data of Construction Projects: Application of a Simulation Model and Singular Spectrum Analysis

2016

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During a construction project life cycle, project costs and time estimations contribute greatly to baseline scheduling. Besides, schedule risk analysis and project control are also influenced by the above factors. Although many papers have offered estimation techniques, little attempt has been made to generate project time series data as daily progressive estimations in different project environments that could help researchers in generating general and customized formulae in further studies. This paper, however, is an attempt to introduce a new simulation approach to reflect the data regarding time series progress of the project, considering the specifications and the complexity of the project and the environment where the project is performed. Moreover, this simulator can equip project managers with estimated information, which reassures them of the execution stages of the project although they lack historical data. A case study is presented to show the usefulness of the model and its applicability in practice. In this study, singular spectrum analysis has been employed to analyze the simulated outputs, and the results are separated based on their signal and noise trends. The signal trend is used as a point-of-reference to compare the outputs of a simulation employing S-curve technique results and the formulae corresponding to earned value management, as well as the life of a given project.

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“…In the required calculations (per iteration of the algorithm) according to the precedence relationship that must be satisfied. stochastic simulation to determine the crash times that minimize the cost of different projects [7], the use simulation to determine optimal resource allocation across several projects in the context of construction industry [8], and pproach to determine optimal resource allocation for the activities of a specific construction project [9,10]. Once again, in all this prior work, only the classical finish to start precedence relationship was assumed.…”

Section: Dss Featuresmentioning

confidence: 99%

Planning and Control of Projects with Different Types of Precedence Relationships and a Service Level Using Stochastic Simulation

Muñoz¹

2015

Proceedings of the International Conference on Computer Information Systems and Industrial Applications

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Abstract-We present a decision support system (DSS) to compute performance measures of a project under uncertainty on the activities' duration as well as four different types of precedence relationships. The DSS generates replicates of the project's performance, in which we simulate the duration of each activity. From these replicates, the expected completion time, the variance of completion time, the service time for a given service level and the probability that each activity will be in the critical path are estimated along with their corresponding measures of accuracy. A validation of the DSS was performed by computing the empirical coverage, mean and standard deviation of halfwidths, mean square error and empirical bias for the main performance metrics of a given project. Our experimental results show that the procedures implemented in the DSS provide a good coverage and consistent half-widths.

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A dynamic crashing method for project management using simulation-based optimization

Cited by 13 publications

References 7 publications

The development of simulation logic model that dealing with uncertainty for piping construction industry

The development of simulation logic model that dealing with uncertainty for piping construction industry

Designing a Framework to Improve Time Series Data of Construction Projects: Application of a Simulation Model and Singular Spectrum Analysis

Planning and Control of Projects with Different Types of Precedence Relationships and a Service Level Using Stochastic Simulation

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