To evaluate the performance of the proposed model in figure 1, we generated 180 small-sized instances and 180 medium-sized instances, and 60 large-sized instances. We generated customer locations in a 1000*1000m2 square. Then randomly assigned to three customer classes. As the second-class and the third-class customers must be covered with the rendezvous locations, we created them in a way that at least one rendezvous node is in sight radius of each second-class or third-class customer. The sight radius is considered to be 100 meters for this data generation. We have defined two locations for the depot as follows: the vertex of the square (0,0) and the center of the square (500,500). We assumed 10 meters per second for truck speed and 20 meters per second for drone speed. In this way, we created 36 various instance types and generated 10 instances for each type.
" authors: - family-names: rashid given-names: reza title: "Benchmark instances for the stochastic hybrid truck-drone routing problem" keywords: version: 1 identifiers: - type: doi value: 10.4121/21646958.v1 license: CC0 date-released: 2022-12-01