Optimizing time related performance measures in logistic problems under uncertainty
Speaker: Ing. Maria Elena Bruni, University of Calabria
Most real-world applications arising in the logistic field are somehow affected by time related parameters.
For example, in the case of emergency aids and perishable products or the delivery of maintenance and repair services, the arrival time is the first concern to deal with. As a time-related factor, the performance of arrival time, is highly affected by parameters which are in nature uncertain.
The fluctuations in the weather condition, traffic congestion, or the vehicle breakdown all have significant impacts on the arrival time and lead us to recognize the travel time as a stochastic parameter. In the seminar, stochastic variants of the k-traveling repairman problem with profits will be analyzed. In this problem, corresponding to each demand node, a profit value is assigned indicating the initial reward associated with the node.
The profit is a function of the random arrival time at the node and, as such, is itself a random variable. The introduction of the uncertainty leads to an increase of the computational complexity of the corresponding mathematical problem making the design of a tailored heuristic solution approach mandatory.
Computational results collected on a set of benchmark instances adapted from the literature and from real case studies will be presented and discussed.
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