Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Control Risk for Multimode Resource-Constrained Project Scheduling Problems under Hybrid Uncertainty
AbstractRisk control in project management has been receiving increasing attention in recent years. This paper proposes an approach based on a risk-assessment program and demonstrates how this can be extended to enhance the multimode resource-constrained project-scheduling problem (MRCPSP) to realize risk control and effective scheduling. The main contribution of this paper is to provide a means to control scheduling and material-purchasing risks by using a bilevel decision framework to identify risk and conduct a focused evaluation. Specifically, this paper establishes a hybrid uncertain multiobjective bilevel programming model and introduces an expected-value operator to deal with the hybrid uncertainty. A multiswarm differential-updating particle swarm optimization is developed to support the model calculations. Worthiness and efficiency of the proposed approach is validated using a case study. This approach can help improve scheduling strategies and ensure realistic project-planning.
Control Risk for Multimode Resource-Constrained Project Scheduling Problems under Hybrid Uncertainty
AbstractRisk control in project management has been receiving increasing attention in recent years. This paper proposes an approach based on a risk-assessment program and demonstrates how this can be extended to enhance the multimode resource-constrained project-scheduling problem (MRCPSP) to realize risk control and effective scheduling. The main contribution of this paper is to provide a means to control scheduling and material-purchasing risks by using a bilevel decision framework to identify risk and conduct a focused evaluation. Specifically, this paper establishes a hybrid uncertain multiobjective bilevel programming model and introduces an expected-value operator to deal with the hybrid uncertainty. A multiswarm differential-updating particle swarm optimization is developed to support the model calculations. Worthiness and efficiency of the proposed approach is validated using a case study. This approach can help improve scheduling strategies and ensure realistic project-planning.
Control Risk for Multimode Resource-Constrained Project Scheduling Problems under Hybrid Uncertainty
Gan, Lu (Autor:in) / Xu, Jiuping
2015
Aufsatz (Zeitschrift)
Englisch
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