A Classified Bibliography Of Research On Stochastic Pert Networks: 1966-1987

Adlakha, Veena; Kulkarni, Vidyadhar G.

doi:10.1080/03155986.1989.11732098

Cited by 62 publications

(51 citation statements)

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“…In the literature on project networks with stochastic activity durations, it is shown (Hagstrom, 1988;Möhring, 2001) that even with independent processing times, the determination of a single point of the cumulative distribution function of project completion time is #P-complete, and thus in particular NP-hard. As noted by Adlakha and Kulkarni (1989), the difficulty arises from two sources: (i) the number of paths grows exponentially in the number of activities; and (ii) even when the activity durations are independent, the path lengths are generally dependent, as several paths have one or more activities in common.…”

Section: Incorporating Risk Preferencesmentioning

confidence: 99%

R&D project scheduling when activities may fail

Reyck

Leus

2008

IIE Transactions

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An R&D project typically consists of several stages. Due to technological risks, the project may have to be terminated before completion, each stage having a specific likelihood of success. In the project planning and scheduling literature, this technological uncertainty has typically been ignored and project plans are developed only for scenarios in which the project succeeds. In this paper we examine how to schedule projects in order to maximize their expected net present value when the project activities have a probability of failure and when an activity's failure leads to overall project termination. We formulate the problem, show that it is NP-hard, develop a branch-and-bound algorithm that allows us to obtain optimal solutions and provide extensive computational results. In the process, we establish a complexity result for an open problem in single-machine scheduling, namely for the discounted weighted-completion-time objective with general precedence constraints.

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Section: Incorporating Risk Preferencesmentioning

confidence: 99%

R&D project scheduling when activities may fail

Reyck

Leus

2008

IIE Transactions

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“…Then the for loop of Algorithm 3 is executed and the float of task (2, 3) is computed in G(1, 3) (the network is constituted by only tasks (1,2) and (2, 3)). Its float is obviously null and then Algorithm 3 assigns the minimal duration to task (3,4).…”

Section: Algorithmmentioning

confidence: 99%

“…Since then, there is an extensive literature on probabilistic PERT (see Elmaghraby [16], and Adlakha and Kulkarni [1] and Elmaghraby [17] for a bibliography and recent views). Even if the task duration times are independent random variables, it is admitted that the problem of finding the distribution of the ending time of a project is intractable, due to the dependencies induced by the topology of the network [24,32,36,40,45].…”

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confidence: 99%

Criticality analysis of activity networks under interval uncertainty

Fortin

Zieliński

Dubois

et al. 2010

J Sched

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“…It relies on basic stochastic analysis approach assuming each activity's duration as a stochastic variable and proposes an approximation method to calculate the cumulative time of the project and its variance. Since its introduction (Malcolm et al, 1959) PERT has been object of wide research work, which delivered numerous variants of the original method with improvement features (Adlakha, 1989;Trietsch and Baker, 2012). However, in the current study, the standard PERT method is applied by offering a first reference of probabilistic analysis.…”

Section: Introductionmentioning

confidence: 99%

Managing the uncertainty in time scheduling of public construction works in Greece

Giannoulis

Salonitis

2015

IJCENT

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Abstract:The construction of public works in Greece usually faces in practice significant deviations from its time scheduling. The aim of this paper is to study and evaluate the possibilities of managing these uncertainties by applying a probabilistic approach mainly based on the method of Monte Carlo simulation. State-of-the-art software was used allowing a better integration of different sources of uncertainty into the time scheduling. The software was applied in an already constructed work and the results were compared with real recorded data. The application demonstrated the strong performance of the Monte Carlo Method and its ability to deal efficiently with uncertainty. The divergence between the results of the Monte Carlo Method and the real data disclosed some structural weaknesses of the ruling framework of public works in Greece that extent the uncertainties. Finally, suggestions are discussed for institutional changes that will assist in a more efficient and accurate time scheduling of the Greek public works.

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A Classified Bibliography Of Research On Stochastic Pert Networks: 1966-1987

Cited by 62 publications

References 0 publications

R&D project scheduling when activities may fail

R&D project scheduling when activities may fail

Criticality analysis of activity networks under interval uncertainty

Managing the uncertainty in time scheduling of public construction works in Greece

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