The efficiency and dynamism of Unmanned Aerial Vehicles (UAVs), or drones, present substantial application opportunities in several industries in the last years. Notably, the logistic companies gave close attention to these vehicles envisioning reduce delivery time and operational cost. A variant of the Traveling Salesman Problem (TSP) called Flying Sidekick Traveling Salesman Problem (FSTSP) was introduced involving drone-assisted parcel delivery. The drone is launched from the truck, proceeds to deliver parcels to a customer and then is recovered by the truck in a third location. While the drone travels through a trip, the truck delivers parcels to other customers as long as the drone has enough battery to hover waiting for the truck. This work proposes a hybrid heuristic that the initial solution is created from the optimal TSP solution reached by a TSP solver. Next, an implementation of the General Variable Neighborhood Search is used to obtain the delivery routes of truck and drone. Computational experiments show the potential of the algorithm to improve the delivery time significantly. Furthermore, we provide a new set of instances based on well-known TSPLIB instances.
The work of @cite_3 envisions reduce delivery time and energy of the work in collaboration of truck and drone (in-tandem system) with the traditional truck delivery (stand-alone). The authors proposed a genetic algorithm (GA) to compute the stand-alone delivery, i.e., the TSP truck route. Furthermore, a K-means algorithm is used to find a solution that combines the truck route with drone nodes.
@cite_3
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Exam timetabling is a computationally intractable problem, which requires heuristic techniques for producing good sub-optimal solutions within reasonable execution time. For large numbers of exams and students, sequential algorithms are likely to be time consuming. The purpose of this work is to present a parallel metaheuristic algorithm for producing good sub-optimal exam timetables in a reasonable time. Empirical results show that our proposed parallel scatter search algorithm yields good speedup. Also, they show that the parallel algorithm improves solution quality in comparison with the sequential algorithm.