Abstract

Due to varying traffic volumes and limited traffic infrastructure in urban areas, travel times generally are uncertain and differ during the day. In this environment, city logistics service providers (CLSP) have to fulfill deliveries cost-efficiently and reliably. To ensure cost-efficient routing while satisfying promised delivery dates, information on expected travel times between customers needs to be exploited. If a sufficient amount of data is not available or expensive to acquire, deriving this information presents a major challenge for CLSP. Therefore, we propose the usage of interval travel times (ITT) to enable cost-efficient and reliable routing in urban areas. ITT define an expected range of travel times, which can be derived with relatively low effort by CLSP. We modify an existing approach from the domain of robust planning to the requirements of routing in urban areas. Further, we present and discuss the process of deriving ITT. An exemplary city logistics setting is developed and different routing solutions are examined. Computational experiments show that, in contrast to well-known deterministic approaches, routing considering ITT allows both cost-efficient and reliable routing.

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