S. Creemers | IESEG School of Management (original) (raw)

Papers by S. Creemers

2011 IEEE International Conference on Industrial Engineering and Engineering Management, 2011

ABSTRACT The goal of project risk management is to provide insight into the risk profile of a pro... more ABSTRACT The goal of project risk management is to provide insight into the risk profile of a project as to facilitate decision makers to mitigate the impact of risks on project objectives such as budget and time. A popular approach to determine where to focus mitigation efforts, is the use of so-called ranking indices. Ranking indices allow the ranking of project activities (or risks) based on the impact they have on project objectives. A distinction needs to be made between activity-based ranking indices (those that rank activities) and risk-driven ranking indices (those that rank risks). Because different ranking indices result in different rankings of activities and risks, one might wonder which ranking index is best? In this article, we provide an answer to this question. Our contribution is threefold: (1) we set up a large computational experiment to assess the efficiency of ranking indices in the mitigation of risks; (2) we develop two new ranking indices that outperform existing ranking indices and (3) we show that a risk-driven approach is more efficient than an activity-based approach.

SSRN Electronic Journal, 2000

ABSTRACT We investigate project scheduling with stochastic activity durations to maximize the exp... more ABSTRACT We investigate project scheduling with stochastic activity durations to maximize the expected net present value. Individual activities also carry a risk of failure, which can cause the overall project to fail. In the project planning literature, such technological uncertainty is typically ignored and project plans are developed only for scenarios in which the project succeeds. To mitigate the risk that an activity’s failure jeopardizes the entire project, more than one alternative may exist for reaching the project’s objectives. We propose a model that incorporates both the risk of activity failure and the possible pursuit of alternative technologies. We find optimal solutions to the scheduling problem by means of stochastic dynamic programming. Our algorithms prescribe which alternatives need to be explored, and how they should be scheduled. We also examine the impact of the variability of the activity durations on the project’s value.

SSRN Electronic Journal, 2000

The production dice game is a powerful learning exercise focusing on the impact of variability an... more The production dice game is a powerful learning exercise focusing on the impact of variability and dependency on throughput and work-in-process inventory of flow lines. In this paper we will extend the basic dice game along the following lines. First, we allow that the operations take place concurrently as opposed to the more traditional way of playing the game sequentially. Second, we allow both starvation and blocking of the line. Third, we consider balanced lines with work stations characterized by different degrees of variability. Fourth, we use different sets of dice in order to represent a wide range of coefficients of variation of the production line. The game can be played manually in a classroom setting, but it is also modelled as an easy-to-use simulation tool.

Annals of Operations Research, 2014

Project risk management aims to provide insight into the risk profile of a project as to facilita... more Project risk management aims to provide insight into the risk profile of a project as to facilitate decision makers to mitigate the impact of risks on project objectives such as budget and time. A popular approach to determine where to focus mitigation efforts, is the use of so-called ranking indices (e.g. the criticality index, the significance index etc.). Ranking indices allow the ranking of project activities (or risks) based on the impact they have on project objectives. A distinction needs to be made between activity-based ranking indices (those that rank activities) and risk-driven ranking indices (those that rank risks). Because different ranking indices result in different rankings of activities and risks, one might wonder which ranking index is best? In this article, we provide an answer to this question. Our contribution is threefold: (1) we set up a large computational experiment to assess the efficiency of ranking indices in the mitigation of risks; (2) we develop two new ranking indices that outperform existing ranking indices and (3) we show that a risk-driven approach is more efficient than an activity-based approach.

2008 IEEE International Conference on Industrial Engineering and Engineering Management, 2008

The literature on project scheduling with uncertain activity durations is still in its burn-in ph... more The literature on project scheduling with uncertain activity durations is still in its burn-in phase. We examine project scheduling with net-present-value objective and exponential activity durations by means of a backward stochastic dynamic programming recursion. We examine the particular setting in which the individual activities carry a risk of failure, and where an activity¿s failure results in the project¿s overall

2011 IEEE International Conference on Industrial Engineering and Engineering Management, 2011

ABSTRACT The goal of project risk management is to provide insight into the risk profile of a pro... more ABSTRACT The goal of project risk management is to provide insight into the risk profile of a project as to facilitate decision makers to mitigate the impact of risks on project objectives such as budget and time. A popular approach to determine where to focus mitigation efforts, is the use of so-called ranking indices. Ranking indices allow the ranking of project activities (or risks) based on the impact they have on project objectives. A distinction needs to be made between activity-based ranking indices (those that rank activities) and risk-driven ranking indices (those that rank risks). Because different ranking indices result in different rankings of activities and risks, one might wonder which ranking index is best? In this article, we provide an answer to this question. Our contribution is threefold: (1) we set up a large computational experiment to assess the efficiency of ranking indices in the mitigation of risks; (2) we develop two new ranking indices that outperform existing ranking indices and (3) we show that a risk-driven approach is more efficient than an activity-based approach.

SSRN Electronic Journal, 2000

ABSTRACT We investigate project scheduling with stochastic activity durations to maximize the exp... more ABSTRACT We investigate project scheduling with stochastic activity durations to maximize the expected net present value. Individual activities also carry a risk of failure, which can cause the overall project to fail. In the project planning literature, such technological uncertainty is typically ignored and project plans are developed only for scenarios in which the project succeeds. To mitigate the risk that an activity’s failure jeopardizes the entire project, more than one alternative may exist for reaching the project’s objectives. We propose a model that incorporates both the risk of activity failure and the possible pursuit of alternative technologies. We find optimal solutions to the scheduling problem by means of stochastic dynamic programming. Our algorithms prescribe which alternatives need to be explored, and how they should be scheduled. We also examine the impact of the variability of the activity durations on the project’s value.

SSRN Electronic Journal, 2000

The production dice game is a powerful learning exercise focusing on the impact of variability an... more The production dice game is a powerful learning exercise focusing on the impact of variability and dependency on throughput and work-in-process inventory of flow lines. In this paper we will extend the basic dice game along the following lines. First, we allow that the operations take place concurrently as opposed to the more traditional way of playing the game sequentially. Second, we allow both starvation and blocking of the line. Third, we consider balanced lines with work stations characterized by different degrees of variability. Fourth, we use different sets of dice in order to represent a wide range of coefficients of variation of the production line. The game can be played manually in a classroom setting, but it is also modelled as an easy-to-use simulation tool.

Annals of Operations Research, 2014

Project risk management aims to provide insight into the risk profile of a project as to facilita... more Project risk management aims to provide insight into the risk profile of a project as to facilitate decision makers to mitigate the impact of risks on project objectives such as budget and time. A popular approach to determine where to focus mitigation efforts, is the use of so-called ranking indices (e.g. the criticality index, the significance index etc.). Ranking indices allow the ranking of project activities (or risks) based on the impact they have on project objectives. A distinction needs to be made between activity-based ranking indices (those that rank activities) and risk-driven ranking indices (those that rank risks). Because different ranking indices result in different rankings of activities and risks, one might wonder which ranking index is best? In this article, we provide an answer to this question. Our contribution is threefold: (1) we set up a large computational experiment to assess the efficiency of ranking indices in the mitigation of risks; (2) we develop two new ranking indices that outperform existing ranking indices and (3) we show that a risk-driven approach is more efficient than an activity-based approach.

2008 IEEE International Conference on Industrial Engineering and Engineering Management, 2008

The literature on project scheduling with uncertain activity durations is still in its burn-in ph... more The literature on project scheduling with uncertain activity durations is still in its burn-in phase. We examine project scheduling with net-present-value objective and exponential activity durations by means of a backward stochastic dynamic programming recursion. We examine the particular setting in which the individual activities carry a risk of failure, and where an activity¿s failure results in the project¿s overall