Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk
In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risks which affect and prevent their desired completio...
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| Veröffentlicht in: | International journal of environmental research and public health 2019-12, Vol.16 (24), p.5024 |
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| container_title | International journal of environmental research and public health |
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| creator | Namazian, Ali Yakhchali, Siamak Haji Yousefi, Vahidreza Tamošaitienė, Jolanta |
| description | In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail. |
| doi_str_mv | 10.3390/ijerph16245024 |
| format | Article |
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Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail.</description><identifier>ISSN: 1660-4601</identifier><identifier>ISSN: 1661-7827</identifier><identifier>EISSN: 1660-4601</identifier><identifier>DOI: 10.3390/ijerph16245024</identifier><identifier>PMID: 31835528</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Bayes Theorem ; Bayesian analysis ; Completion time ; Computer Simulation ; Construction ; Construction industry ; Construction Industry - organization & administration ; Delphi method ; Enterprise resource planning ; Fuzzy sets ; Humans ; Methods ; Monte Carlo Method ; Monte Carlo simulation ; Multiple criteria decision making ; Probability ; Project engineering ; Refineries ; Risk assessment ; Sensitivity analysis ; Time Factors</subject><ispartof>International journal of environmental research and public health, 2019-12, Vol.16 (24), p.5024</ispartof><rights>2019. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). 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Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail.</description><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Completion time</subject><subject>Computer Simulation</subject><subject>Construction</subject><subject>Construction industry</subject><subject>Construction Industry - organization & administration</subject><subject>Delphi method</subject><subject>Enterprise resource planning</subject><subject>Fuzzy sets</subject><subject>Humans</subject><subject>Methods</subject><subject>Monte Carlo Method</subject><subject>Monte Carlo simulation</subject><subject>Multiple criteria decision making</subject><subject>Probability</subject><subject>Project engineering</subject><subject>Refineries</subject><subject>Risk assessment</subject><subject>Sensitivity analysis</subject><subject>Time Factors</subject><issn>1660-4601</issn><issn>1661-7827</issn><issn>1660-4601</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpdkc1P3DAQxS1EBXTLlWNliUsvSx2PYzuXSnTVLwkKaunZchyb9ZLYW0_Siv--oVAEPc1I85s38_QIOarYCUDD3saNL9t1JbmoGRc75KCSki2FZNXuk36fvETcMAZayGaP7EOloa65PiC4ykMbU0zX9Dyn0dOVLX2m3-Mw9XaMOVGbOvre3nqMNtGvfvydyw3Scz-uc4c05EJPET3incQstu3937WrOHiaA70seePdiHRKnS_0W8SbV-RFsD36w4e6ID8-frhafV6eXXz6sjo9WzpR6XEZlGyYcEy1tVMgXNBBtcwqHaBTnDfQSAsaoAMIQQglglBdE1zgXcXaWsGCvLvX3U7t4Dvn01hsb7YlDrbcmmyjeT5JcW2u8y8jm5rJ-cCCvHkQKPnn5HE0Q0Tn-94mnyc0HEDymjMBM3r8H7rJU0mzvZnijZRaKD1TJ_eUKxmx-PD4TMXMXZ7meZ7zwuunFh7xfwHCH2YHni4</recordid><startdate>20191210</startdate><enddate>20191210</enddate><creator>Namazian, Ali</creator><creator>Yakhchali, Siamak Haji</creator><creator>Yousefi, Vahidreza</creator><creator>Tamošaitienė, Jolanta</creator><general>MDPI AG</general><general>MDPI</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-5957-0620</orcidid><orcidid>https://orcid.org/0000-0003-4692-6821</orcidid></search><sort><creationdate>20191210</creationdate><title>Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk</title><author>Namazian, Ali ; 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Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. 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| subjects | Bayes Theorem Bayesian analysis Completion time Computer Simulation Construction Construction industry Construction Industry - organization & administration Delphi method Enterprise resource planning Fuzzy sets Humans Methods Monte Carlo Method Monte Carlo simulation Multiple criteria decision making Probability Project engineering Refineries Risk assessment Sensitivity analysis Time Factors |
| title | Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk |
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