{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/106219"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/106219","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Risk management of repetitive construction projects","abstract":"Repetitive construction projects such as highways, high-rise buildings, and housing projects consist of repetitive construction activities that need to be repeated by the same crew in several locations in the project. Repetitive construction projects have inherent uncertainties that are commonly encountered during the construction phase due to variations in labor productivity, weather, site conditions, and equipment availability. These inherent uncertainties often lead to project delays and additional cost. The main goal of this study is to present the development of novel models to analyse the impacts of activity delays and optimize resource utilization with its stochastic scheduling in repetitive construction projects. To achieve this goal, the research objectives of this study are to develop: (1) a novel scheduling model for both serial and non-serial repetitive construction projects to quantify the impact of any activity delay on interrupting the crew work continuity of its successors; (2) an innovative stochastic scheduling model for repetitive construction projects to analyze and optimize the impact of crew deployment dates in uncertain repetitive construction projects on the project duration and the work continuity of construction crews and their impacts on project cost; and (3) a novel multi-objective stochastic scheduling optimization model for both serial and non-serial repetitive construction projects that is capable of searching for and identifying an optimal/near optimal crew formation and its deployment date for each activity that that generates optimal tradeoffs between project duration and project cost. The performance of the developed models was analyzed using real-life case studies. The results of analyzing these case studies illustrated the novel, and unique capabilities of the developed models in enabling construction planners and managers to (1) classify project activities according to the severity of their delay impact, (2) minimize negative impacts of activity delays, (3) maximize crew work continuity, (4) maximize resource utilization, (5) minimize project duration and (6) minimize project cost.","abstract_html":"Repetitive construction projects such as highways, high-rise buildings, and housing projects consist of repetitive construction activities that need to be repeated by the same crew in several locations in the project. Repetitive construction projects have inherent uncertainties that are commonly encountered during the construction phase due to variations in labor productivity, weather, site conditions, and equipment availability. These inherent uncertainties often lead to project delays and additional cost. The main goal of this study is to present the development of novel models to analyse the impacts of activity delays and optimize resource utilization with its stochastic scheduling in repetitive construction projects. To achieve this goal, the research objectives of this study are to develop: (1) a novel scheduling model for both serial and non-serial repetitive construction projects to quantify the impact of any activity delay on interrupting the crew work continuity of its successors; (2) an innovative stochastic scheduling model for repetitive construction projects to analyze and optimize the impact of crew deployment dates in uncertain repetitive construction projects on the project duration and the work continuity of construction crews and their impacts on project cost; and (3) a novel multi-objective stochastic scheduling optimization model for both serial and non-serial repetitive construction projects that is capable of searching for and identifying an optimal/near optimal crew formation and its deployment date for each activity that that generates optimal tradeoffs between project duration and project cost. The performance of the developed models was analyzed using real-life case studies. The results of analyzing these case studies illustrated the novel, and unique capabilities of the developed models in enabling construction planners and managers to (1) classify project activities according to the severity of their delay impact, (2) minimize negative impacts of activity delays, (3) maximize crew work continuity, (4) maximize resource utilization, (5) minimize project duration and (6) minimize project cost.","abstract_has_math":false,"creators":["Hassan, Abbas Atef Abbas"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["El-Rayes, Khaled","Liu, Liang","El-Gohary, Nora","Golparvar-Fard, Mani","Attalla, Mohamed"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-03-02T21:58:17Z","date_published":"2020-03-02T21:58:17Z","updated_at":"2026-07-22T22:24:45Z","subjects":["Non-Serial Repetitive Construction Projects","Linear Scheduling","Crew work continuity","Float","Delay Impact","Construction Management","Stochastic models","Monte Carlo simulation","Crew deployment date","Resource Utilization Plan","Optimization","Genetic algorithms"],"languages":["en"],"rights":["Copyright 2019 Abbas Hassan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/106219","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["El-Rayes, Khaled","Liu, Liang","El-Gohary, Nora","Golparvar-Fard, Mani","Attalla, Mohamed"]},{"key":"dc:creator","label":"Author","values":["Hassan, Abbas Atef Abbas"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-03-02T21:58:17Z","2019-11-26","2019-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Non-Serial Repetitive Construction Projects","Linear Scheduling","Crew work continuity","Float","Delay Impact","Construction Management","Stochastic models","Monte Carlo simulation","Crew deployment date","Resource Utilization Plan","Optimization","Genetic algorithms"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Abbas Hassan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/106219"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Repetitive construction projects such as highways, high-rise buildings, and housing projects consist of repetitive construction activities that need to be repeated by the same crew in several locations in the project. Repetitive construction projects have inherent uncertainties that are commonly encountered during the construction phase due to variations in labor productivity, weather, site conditions, and equipment availability. These inherent uncertainties often lead to project delays and additional cost. The main goal of this study is to present the development of novel models to analyse the impacts of activity delays and optimize resource utilization with its stochastic scheduling in repetitive construction projects. To achieve this goal, the research objectives of this study are to develop: (1) a novel scheduling model for both serial and non-serial repetitive construction projects to quantify the impact of any activity delay on interrupting the crew work continuity of its successors; (2) an innovative stochastic scheduling model for repetitive construction projects to analyze and optimize the impact of crew deployment dates in uncertain repetitive construction projects on the project duration and the work continuity of construction crews and their impacts on project cost; and (3) a novel multi-objective stochastic scheduling optimization model for both serial and non-serial repetitive construction projects that is capable of searching for and identifying an optimal/near optimal crew formation and its deployment date for each activity that that generates optimal tradeoffs between project duration and project cost. The performance of the developed models was analyzed using real-life case studies. The results of analyzing these case studies illustrated the novel, and unique capabilities of the developed models in enabling construction planners and managers to (1) classify project activities according to the severity of their delay impact, (2) minimize negative impacts of activity delays, (3) maximize crew work continuity, (4) maximize resource utilization, (5) minimize project duration and (6) minimize project cost.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-02-28 without embargo terms","The student, Abbas Hassan, accepted the attached license on 2019-11-25 at 18:42.","The student, Abbas Hassan, submitted this Dissertation for approval on 2019-11-25 at 19:01.","This Dissertation was approved for publication on 2019-11-26 at 10:55.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14618 on 2020-02-28 at 17:14:23","Made available in DSpace on 2020-03-02T21:58:17Z (GMT). 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Repetitive construction projects have inherent uncertainties that are commonly encountered during the construction phase due to variations in labor productivity, weather, site conditions, and equipment availability. These inherent uncertainties often lead to project delays and additional cost. The main goal of this study is to present the development of novel models to analyse the impacts of activity delays and optimize resource utilization with its stochastic scheduling in repetitive construction projects. To achieve this goal, the research objectives of this study are to develop: (1) a novel scheduling model for both serial and non-serial repetitive construction projects to quantify the impact of any activity delay on interrupting the crew work continuity of its successors; (2) an innovative stochastic scheduling model for repetitive construction projects to analyze and optimize the impact of crew deployment dates in uncertain repetitive construction projects on the project duration and the work continuity of construction crews and their impacts on project cost; and (3) a novel multi-objective stochastic scheduling optimization model for both serial and non-serial repetitive construction projects that is capable of searching for and identifying an optimal/near optimal crew formation and its deployment date for each activity that that generates optimal tradeoffs between project duration and project cost. The performance of the developed models was analyzed using real-life case studies. The results of analyzing these case studies illustrated the novel, and unique capabilities of the developed models in enabling construction planners and managers to (1) classify project activities according to the severity of their delay impact, (2) minimize negative impacts of activity delays, (3) maximize crew work continuity, (4) maximize resource utilization, (5) minimize project duration and (6) minimize project cost.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-02-28 without embargo terms","The student, Abbas Hassan, accepted the attached license on 2019-11-25 at 18:42.","The student, Abbas Hassan, submitted this Dissertation for approval on 2019-11-25 at 19:01.","This Dissertation was approved for publication on 2019-11-26 at 10:55.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14618 on 2020-02-28 at 17:14:23","Made available in DSpace on 2020-03-02T21:58:17Z (GMT). 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