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to analyze the performance of the proposed solution approach under varying
conditions. For the new instances generated for the computational study, CTP
can achieve a cost reduction of about 6.5% for all settings. CTP is especially
preferable when the environment is highly dynamic. It is further suggested to
use advance information on requests by performing forward-looking planning for
better results. However, only requests that are to be fulfilled in the near fu-
ture should be considered. This can reduce the computational efforts needed for
the planning without harming the quality of the planning. In the future, more
computational experiments have to be conducted to specify the key factors that
affect the performance of the proposed approach for the DCTPP. An example
of such factors is the definition of due requests. Further factors that need to be
studied include time window width and different cost level of subcontracting.
Acknowledgments.
This research was supported by the German Research
Foundation (DFG) as part of the project “Kooperative Rundreiseplanung bei
rollierender Planung”.
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