On the sensitivity of project variability to activity mean duration

Elmaghraby, Salah E.; Fathi, Yahya; Taner, Mehmet R.

doi:10.1016/s0925-5273(98)00241-2

Cited by 38 publications

(17 citation statements)

References 11 publications

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“…Cho and Yum [109] propose an uncertainty importance measure to measure the effect of the variability in an activity's duration on the variability of the overall project duration. Elmaghraby et al [110] investigate the impact of changing the mean duration of an activity on the variability of the project duration. Finally, Gutierrez and Paul [111] present an analytical treatment of the effect of activity variance on the expected project duration.…”

Section: Test Datamentioning

confidence: 99%

An Overview of Recent Research Results and Future Research Avenues Using Simulation Studies in Project Management

Vanhoucke

2013

ISRN Computational Mathematics

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This paper gives an overview of three simulation studies in dynamic project scheduling integrating baseline scheduling with risk analysis and project control. This integration is known in the literature as dynamic scheduling. An integrated project control method is presented using a project control simulation approach that combines the three topics into a single decision support system. The method makes use of Monte Carlo simulations and connects schedule risk analysis (SRA) with earned value management (EVM). A corrective action mechanism is added to the simulation model to measure the efficiency of two alternative project control methods. At the end of the paper, a summary of recent and state-of-the-art results is given, and directions for future research based on a new research study are presented.

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Section: Test Datamentioning

confidence: 99%

An Overview of Recent Research Results and Future Research Avenues Using Simulation Studies in Project Management

Vanhoucke

2013

ISRN Computational Mathematics

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“…One different element that might create concerns to the decision maker is the variability of the outcomes but, to the best of our knowledge, variability has by itself to date never been studied in the context of stochastic resource-constrained project scheduling except for Ballestín and Leus [3], who observe a trade-off between expected makespan and makespan variability. For the record, we should point out that makespan variance has been studied in the absence of resource constraints, notably by Elmaghraby et al [11], who distinguish both mean and variance of the project duration as the two prime performance measures of concern, by Gutierrez and Paul [17], who examine the impact of variability in activity durations on mean project duration, and by Cho and Yum [6], whose focus is more on the sensitivity of makespan variability.…”

Section: Esmentioning

confidence: 99%

A Novel Class of Scheduling Policies for the Stochastic Resource-Constrained Project Scheduling Problem

2008

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We study the resource-constrained project scheduling problem with stochastic activity durations. We introduce a new class of scheduling policies for this problem, which make a number of a-priori sequencing decisions in a pre-processing phase, while the remaining decisions are made dynamically during project execution. The pre-processing decisions entail the addition of precedence constraints to the scheduling instance, hereby resolving some potential resource conflicts. We compare the performance of this new class with existing scheduling policies for the stochastic resource-constrained project scheduling problem, and we observe that the new class is significantly better when the variability in the activity durations is medium to high.

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“…This included criticism of PERT and the beta-distribution [29][30][31], and the treatment of project management as being not only deterministic [32]. The modeling of the uncertainty of project phenomena began to be considered as assumptions about attributes considered static broadened [33][34][35][36][37][38][39]. System dynamics began to be used for modeling the nonlinear effects of feedback loops in projects [40][41][42][43] and the modeling of projects under diffuse or probabilistic assumptions [44][45][46][47][48].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of Project Management through the PMBOK® Standard Using Complex Networks

Cardona-Meza

Tost

2017

Complexity

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Discussion about project management, in both the academic literature and industry, is predominantly based on theories of control, many of which have been developed since the 1950s. However, issues arise when these ideas are applied unilaterally to all types of projects and in all contexts. In complex environments, management problems arise from assuming that results, predicted at the start of a project, can be sufficiently described and delivered as planned. Thus, once a project reaches a critical size, a calendar, and a certain level of ambiguity and interconnection, the analysis centered on control does not function adequately. Projects that involve complex situations can be described as adaptive complex systems, consistent in multiple interdependent dynamic components, multiple feedback processes, nonlinear relations, and management of hard data (process dynamics) and soft data (executive team dynamics). In this study, through a complex network, the dynamic structure of a project and its trajectories are simulated using inference processes. Finally, some numerical simulations are described, leading to a decision making tool that identifies critical processes, thereby obtaining better performance outcomes of projects.

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On the sensitivity of project variability to activity mean duration

Cited by 38 publications

References 11 publications

An Overview of Recent Research Results and Future Research Avenues Using Simulation Studies in Project Management

An Overview of Recent Research Results and Future Research Avenues Using Simulation Studies in Project Management

A Novel Class of Scheduling Policies for the Stochastic Resource-Constrained Project Scheduling Problem

Modeling and Simulation of Project Management through the PMBOK® Standard Using Complex Networks

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