Abstract
The fast and cost-ecient home delivery of goods ordered online is logistically chal-
lenging. Many companies are looking for new ways to cross the last-mile to their
customers. One technology-enabled opportunity that recently has received much at-
tention is the use of a drone to support deliveries. An innovative last-mile delivery
concept in which a truck collaborates with a drone to make deliveries gives rise to
a new variant of the traveling salesman problem (TSP) that we call the TSP with
drone. In this paper, we model this problem as an IP and develop several fast route
rst-cluster second heuristics based on local search and dynamic programming. We
prove worst-case approximation ratios for the heuristics and test their performance
by comparing the solutions to the optimal solutions for small instances. In addition,
we apply our heuristics to several articial instances with dierent characteristics and
sizes. Our experiments show that substantial savings are possible with this concept in
comparison to truck-only delivery.
Original language | English |
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Pages (from-to) | 965-981 |
Number of pages | 17 |
Journal | Transportation Science |
Volume | 52 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2018 |
Research programs
- RSM LIS