research
A Quasi-Robust Optimization Approach for Resource Rescheduling
- Publication date
- 1 November 2013
- Publisher
- If a disruption takes place in a complex task-based system, where tasks are carried out
by a number of resource units or servers, real-time disruption management usually has
to deal with an uncertain duration of the disruption. In this paper we present a novel
approach for rescheduling such systems, thereby taking into account the uncertain duration
of the disruption. We assume that several possibilities for the duration of the
disruption are given.
We solve the rescheduling problem as a two-stage optimization problem. In the
first stage, at the start of the disruption, we reschedule the plan based on the optimistic
scenario for the duration of the disruption, while taking into account the possibility
that another scenario will be realized. In fact, we require a prescribed number of the
rescheduled resource duties to be recoverable. This means that they can be easily
recovered if it turns out that another scenario than the optimistic one is realized.
We demonstrate the effectiveness of our approach by an application in real-time
railway crew rescheduling. This is an important subproblem in the disruption management
process of a railway company with a lot of uncertainty about the duration of a
disruption. We test our approach on a number of instances of Netherlands Railways (NS), the main operator of passenger trains in the Netherlands. The numerical experiments
show that the approach indeed finds schedules which are easier to adjust if it
turns out that another scenario than the optimistic one is realized.