Integrating uncertainty aspects into schedule optimization

Leonid Jasvoin

2006

The fierce competition in today's markets requires companies to provide time and cost-optimized services and to allocate resources efficiently. However, many of the schedule-optimization models developed for this purpose fail because they assume that either the scheduling parameters remain constant or the distribution of these parameters over the relevant period is known. But this does not correspond to the reality of how things work.

Using the aviation industry as an example, Leonid Jasvoin develops a model for integrating uncertainty aspects comprehensively, realistically and with a sound theoretical basis into flight-schedule optimization. The uncertainties relating to departure and arrival times of flights are mapped using the fuzzy-quantity theory. This allows both past information and subjective ideas, experiences and evaluations by experts to be taken into account in deriving statements about the expected uncertainties.