An overview of recent research results and future research avenues using simulation studies in project management

This paper gives an overview of three simulation studies in dynamic project scheduling integrating baseline scheduling with risk analysis and project control. This integration is known in the literature as dynamic scheduling. An integrated project control method is presented using a project control simulation approach that combines the three topics into a single decision support system. The method makes use of Monte Carlo simulations and connects schedule risk analysis (SRA) with earned value management (EVM). A corrective action mechanism is added to the simulation model to measure the efficiency of two alternative project control methods. At the end of the paper, a summary of recent and state-of-the-art results is given, and directions for future research based on a new research study are presented

Meta-heuristic based Construction Supply Chain Modelling and Optimization

Driven by the severe competition within the construction industry, the necessity of improving and optimizing the performance of construction supply chain has been aroused. This thesis proposes three problems with regard to the construction supply chain optimization from three perspectives, namely, deterministic single objective optimization, stochastic optimization and multi-objective optimization respectively. Mathematical models for each problem are constructed accordingly and meta-heuristic algorithms are developed and applied for resolving these three problems

Improving decision making for incentivised and weather-sensitive projects

The field of project management has originated from the domain of operational research, which focuses on the mathematical optimization of operational problems. However, in recent decades an increasingly broad perspective has been applied to the field of project management. As such, project management has spawned a number of very active sub- domains, which focus not solely on the scheduling of the project’s baseline, but also on the analysis of risk, as well as the controlling of project execution. This dissertation focuses on two areas where existing literature is still lacking. The first area is the use of incentivised contractual agreements between the owner of a project, and the contractor who is hired to execute the project. Whereas this area has received growing attention in recent years, the majority of studies remained strongly descriptive. Hence, the aim of the first part of this dissertation is to develop a more prescriptive approach from both the owner’s and the contractor’s perspective. The second part of this dissertation investigates the use of dedicated weather models to improve operational performance of weather-sensitive projects. During recent decades, significant effort has been made to improve the quality of weather simulation models. Moreover, the amount of available weather data has been steadily increasing. This opens up a lot of new possibilities for using more precise weather models in order to support operational decision making. In spite of this, the number of applications of these weather models in operational research has remained rather limited. As such, the aim of the second part of this dissertation is to leverage these weather models to improve the scheduling of offshore construction projects, as well as preventive maintenance of offshore wind turbines