Efficient Monte Carlo simulation method of GERT-type network for project management

Kurihara, Kenzo; Nishiuchi, Nobuyuki

doi:10.1016/s0360-8352(02)00050-5

Cited by 53 publications

(24 citation statements)

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“…In other words, the left shape function is non-decreasing and the right shape function is non-increasing. This assures the convexity of e D. Consequently, the membership function of e D can be constructed from the optimal solutions of Models (12) and (14). Note that these optimal solutions are parameterized by a.…”

Section: Finding the Fuzzy Total Duration Timementioning

confidence: 99%

“…This can be extended to fuzzy environments. Critical paths at each possibility level a could be identified from the optimal solution of Models (12) and (14); in this paper, we call them fuzzy critical paths. For Model (12), the critical activities correspond to the constraints that are satisfied as strict equations by the obtained optimal solution, i.e., the critical path for this project network consists of a path from the start of the project to the finish in which each arc in the path corresponds to a constraint having a dual price of À1 [21].…”

Section: Finding the Fuzzy Critical Pathsmentioning

confidence: 99%

“…This means that if any critical activity time is increased by 1 unit time, the total duration time of this project will be delayed for 1 unit time. For Model (14), the critical path for this project network consists of an activity (i, j) 2 A from the start to the finish in which each activity in the path corresponds to the optimal decision variable x Ã ij ¼ 1. Consequently, at each possibility level a, at least one critical path can be found for the lower bound of the fuzzy total duration time and at least one for the upper bound of the fuzzy total duration time.…”

Section: Finding the Fuzzy Critical Pathsmentioning

confidence: 99%

“…However, there are many cases where the activity times may not be presented in a precise manner. To deal quantitatively with imprecise data, the program evaluation and review technique (PERT) [11,13] and Monte Carlo simulation (e.g., [14,16]) based on the probability theory can be employed. However, there are critiques of PERT [6,17].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of critical paths in a project network with fuzzy activity times

Chen

2007

European Journal of Operational Research

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Section: Finding the Fuzzy Total Duration Timementioning

confidence: 99%

Section: Finding the Fuzzy Critical Pathsmentioning

confidence: 99%

Section: Finding the Fuzzy Critical Pathsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Analysis of critical paths in a project network with fuzzy activity times

Chen

2007

European Journal of Operational Research

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“…As investment projects consist of various uncertain jobs, only simulation technique can analyse the random characteristics of practical project model [9]. The paper by [10] established a nuclear power investment evaluation model by employing real options theory with Monte Carlo method.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Economic Efficiency of the Modernization of Crushed Stone Manufacturing Process: Case Study

Fabianová¹,

Janeková²,

Fábián³

2018

Adv. Sci. Technol. Res. J.

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The aim of the paper is to evaluate the economic efficiency of the proposed modernization of the production process of crushed stone in the quarry and to decide whether to accept it or reject it. The project is assessed in a complex way. Profitability is evaluated using Net Present Value (NPV) and Profitability Index (PI), liquidity by means of Discounted Payback Period (DPP). The risk associated with the respective investment is assessed using a probabilistic method -Monte Carlo simulation.

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Assessing Performance Risk for Complex Product Development: A Simulation‐Based Model

2012

Quality & Reliability Eng

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Assessing and managing performance risk is important for complex product development projects. The performance risk of complex product development can be defined as the probability failing to achieve desired performance level subject to cost and time constraints. This article presents a simulation model based on the graphical evaluation and review technique (GERT) and analyzes the complex product development project using simulation data. The model computes the probability distribution of project duration and cost in a GERT network with multifeedback branches considering activities rework that is caused by probabilistic failure to meet the planned design objective. A simulation strategy is designed to assess the performance risk in both subsystems and system development. With the performance risk assessment methodology, project managers can make a better decision and then minimize the performance risk of product development project. Finally, an obstacle clearance armored vehicle development project is used to illustrate the effectiveness of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.

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Efficient Monte Carlo simulation method of GERT-type network for project management

Cited by 53 publications

References 0 publications

Analysis of critical paths in a project network with fuzzy activity times

Analysis of critical paths in a project network with fuzzy activity times

Assessment of the Economic Efficiency of the Modernization of Crushed Stone Manufacturing Process: Case Study

Assessing Performance Risk for Complex Product Development: A Simulation‐Based Model

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