A decision-making tool to maximize chances of meeting project commitments

Nguyen, Khanh T. P.; Marmier, François; Gourc, Didier

doi:10.1016/j.ijpe.2010.11.023

Cited by 30 publications

(28 citation statements)

References 13 publications

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“…Some researchers used the Bayesian Network (BN) modelling framework for assessing project risk and uncertainty [21][22][23][24]. Nguyen et al [25] developed ProRisk methodology which serves as a decisionmaking tool to choose the best risk treatment strategy. In [26], authors used a probabilistic fuzzy method and fuzzy IF-THEN rules for innovative project risk assessment while Rodríguez et al [27] employed a combination of Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Inference System (FIS) for assessing risks of information technology projects.…”

Section: Methods For Assessment and Management Of Risk And Uncertaintymentioning

confidence: 99%

Simulating the Impact of Activity Uncertainties and Risk Combinations in R&D Projects

Chenarani¹,

Дружинин²,

Kritskiy³

2017

JESTR

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The quantifiable consequences of uncertainty are simulated and analyzed for R&D projects. These consequences include variation in duration and cost of activities and the presence of risk factors in project. Categorizing risks into four types is proposed according to their impact on the main constraints of the project. The most prominent type of risk in R&D projects is the rework risk but common software packages for project management are not able to simulate them. A discrete event based Monte Carlo simulation method is employed for project simulation. The required project and risk data for simulation are represented by means of dependency structure matrix (DSM). For calculating the effects of rework risk, BFS graph traversal algorithm is used. A simulation program is developed and implemented in a small turbojet engine preliminary design project. The results of this research can improve the effectiveness of decision-making process by project manager where choosing appropriate method for reducing risk effects under uncertainty conditions is required.

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Section: Methods For Assessment and Management Of Risk And Uncertaintymentioning

confidence: 99%

Simulating the Impact of Activity Uncertainties and Risk Combinations in R&D Projects

Chenarani¹,

Дружинин²,

Kritskiy³

2017

JESTR

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“…For large engineering projects, a network theory based approach was presented in to deal with the interdependencies between negative risks and to better understand their potential interactions by using network theory indicators in project risk analysis. In Nguyen et al (2013), the ProRisk methodology has been developed to provide to project managers a decision making tool to select the best risk treatment strategy. In the same context, in Fan et al (2008) an analytical model based on a conceptual framework that describes the quantitative relationships between risk-handling strategy and the various project characteristics (technical complexity, project size, slack) has been proposed.…”

Section: Related Workmentioning

confidence: 99%

A risk-based approach applied to system engineering projects: A new learning based multi-criteria decision support tool based on an Ant Colony Algorithm

Lachhab

Béler

Coudert

2018

Engineering Applications of Artificial Intelligence

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This is an author-deposited version published in: http://oatao.univ-toulouse.fr/ Eprints ID: 19945 A B S T R A C TThis article proposes a multi-criteria decision support tool fully integrated within system engineering and project management processes that allows decision makers to select an optimal scenario of a project. A model based on an oriented graph includes all the alternative choices of a new system's conception and realization. These choices take into account the risks inherent to perform project tasks in terms of cost and duration. The model of the graph is constructed by considering all the collaborative decisions of the different actors involved in the project. This decision support tool is based on an Ant Colony Algorithm (ACO) for its ability to provide optimal solutions in a reasonable amount of time. The model developed is a multi-objective new ant colony algorithm based on an innovative learning mechanism (named MONACO) that allows ants to learn from their previous choices in order to influence the future ones. The objectives to be minimized are the total cost of the project, its global duration and the risk associated with these criteria. The risk is modeled as an uncertainty related to the increase of the nominal values of cost and duration. The optimization tool is a part of an integrated and more global process, based on industrial standards (the System Engineering process and the Project Management one) that are widely known and used in companies.

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“…Risk is described as an event, which has occurrence characteristics (potentiality to occur) and consequence characteristics on the project objectives (impact in the event of occurrence). Nguyen et al [25] propose Prorisk, which can model and evaluate the impact of risks on the project cost and the schedule cost. They define the concepts of risk scenario, treatment scenario and project scenario.…”

Section: Dealing With Project Risk Managementmentioning

confidence: 99%

“…Finally, when the project scenarios are known it is possible to obtain their durations and costs. The approach called ProRisk proposed in [25] is then used to generate E ScP v . For each project scenario, the calculation of the probability, the cost and the duration take into account the potential modifications induced by the achievement of treatment strategies at the schedule level.…”

Section: (A)mentioning

confidence: 99%

A risk oriented model to assess strategic decisions in new product development projects

Marmier

Gourc

Laarz

2013

Decision Support Systems

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The project management team has to respect contractual commitments, in terms of deadlines and budgets, that are often two antagonistic objectives. At the same time, the market becomes more and more demanding as far as costs and delays are concerned while expecting a high quality level. Then, the project management team has to continuously consider novelty and a risk management strategy in order to determine the best balance between benefits and risks. Based on the principles of a synchronized process between risk management and project management, and on the concepts of risk scenario, we propose a decision-making tool to help the project manager choose the best way to improve project success rate while controlling the level of risks. As a finding, the project manager would be able to evaluate and compare different novelties or development strategies taking into account their repercussions on potential risks and risk treatment strategies. Finally, a case study in the aerospace industry and specifically on satellite integration and tests is developed to validate this approach.

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A decision-making tool to maximize chances of meeting project commitments

Cited by 30 publications

References 13 publications

Simulating the Impact of Activity Uncertainties and Risk Combinations in R&D Projects

Simulating the Impact of Activity Uncertainties and Risk Combinations in R&D Projects

A risk-based approach applied to system engineering projects: A new learning based multi-criteria decision support tool based on an Ant Colony Algorithm

A risk oriented model to assess strategic decisions in new product development projects

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