A collaborative tandem truck multi-drone for logistics problems


Once the technological and economic viability of UAVs in the mass market has been achieved, sectors in which last mile logistics has a great weight within their operating costs have shown to be making great efforts to progress in the implementation of the use of UAVs in their ecosystem. Proof of this are the numerous videos in which companies such as Amazon showed the world their still primitive idea of the logistics of the future, with drones delivering directly to private homes. However, and always depending on in which direction the system is focused, all approaches to drone logistics present enormous operational challenges that have not yet been fully solved, opening up a very broad and interesting field of research.


Our research is focused on the last mile collaborative logistics between a truck and several drones with limited autonomy, wherein both the truck and the drones make deliveries simultaneously and the drones use the truck as a mobile battery change station that allows them to fully recover their autonomy.

We propose an optimization-based approach to this TMDTL problem and develop an iterated greedy heuristic supported in turn by a bivector coding based on a binary approach as and efficient method for its resolution.

We have evolved from the problem known in the literature as TDTL to implement an encoding that would allow the use of any number of drones while maintaining the simplicity in the resolution and, therefore, the speed of resolution of the original approach.

Once a suitable encoding has been established, an iterated greedy heuristic controlled by a simulated annealing algorithm is applied to obtain fast and high-quality solutions.


As expected, the use of the developed iterated greedy heuristics has led us to achieve the fast resolution of the challenging TMDTL. It is observed that a smaller temperature gradient in the simulated annealing algorithm does not necessarily imply better results. Further experimentation and statistical analysis are projected.


After performing a punctual experimentation on a uniform instance with 20 service points, it can be observed how in the solutions the use of several drones results in a shorter distance travelled by the truck as well as a shorter total service time of the set of customers.

Palabras clave

Drones Logistics Optimization

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David Sanchez-Wells

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