4,548 research outputs found
An ACO-Inspired, Probabilistic, Greedy Approach to the Drone Traveling Salesman Problem
In recent years, major companies have done research on using drones for parcel delivery. Research has shown that this can result in significant savings, which has led to the formulation of various truck and drone routing and scheduling optimization problems. This paper explains and analyzes a new approach to the Drone Traveling Salesman Problem (DTSP) based on ant colony optimization (ACO).
The ACO-based approach has an acceptance policy that maximizes the usage of the drone. The results reveal that the pheromone causes the algorithm to converge quickly to the best solution. The algorithm performs comparably to the MIP model, CP model, and EA of Rich & Ham (2018), especially in instances with a larger number of stops
Multiservice UAVs for Emergency Tasks in Post-disaster Scenarios
UAVs are increasingly being employed to carry out surveillance, parcel
delivery, communication-support and other specific tasks. Their equipment and
mission plan are carefully selected to minimize the carried load an overall
resource consumption. Typically, several single task UAVs are dispatched to
perform different missions. In certain cases, (part of) the geographical area
of operation may be common to these single task missions (such as those
supporting post-disaster recovery) and it may be more efficient to have
multiple tasks carried out as part of a single UAV mission using common or even
additional specialized equipment.
In this paper, we propose and investigate a joint planning of multitask
missions leveraging a fleet of UAVs equipped with a standard set of accessories
enabling heterogeneous tasks. To this end, an optimization problem is
formulated yielding the optimal joint planning and deriving the resulting
quality of the delivered tasks. In addition, a heuristic solution is developed
for large-scale environments to cope with the increased complexity of the
optimization framework. The developed joint planning of multitask missions is
applied to a specific post-disaster recovery scenario of a flooding in the San
Francisco area. The results show the effectiveness of the proposed solutions
and the potential savings in the number of UAVs needed to carry out all the
tasks with the required level of quality
A Hybrid Genetic Algorithm for the Traveling Salesman Problem with Drone
This paper addresses the Traveling Salesman Problem with Drone (TSP-D), in
which a truck and drone are used to deliver parcels to customers. The objective
of this problem is to either minimize the total operational cost (min-cost
TSP-D) or minimize the completion time for the truck and drone (min-time
TSP-D). This problem has gained a lot of attention in the last few years since
it is matched with the recent trends in a new delivery method among logistics
companies. To solve the TSP-D, we propose a hybrid genetic search with dynamic
population management and adaptive diversity control based on a split
algorithm, problem-tailored crossover and local search operators, a new restore
method to advance the convergence and an adaptive penalization mechanism to
dynamically balance the search between feasible/infeasible solutions. The
computational results show that the proposed algorithm outperforms existing
methods in terms of solution quality and improves best known solutions found in
the literature. Moreover, various analyses on the impacts of crossover choice
and heuristic components have been conducted to analysis further their
sensitivity to the performance of our method.Comment: Technical Report. 34 pages, 5 figure
Usage and acceptance of drone technology in healthcare : exploring patients and physicians perspective
Modern technologies such as virtual reality, robots or drones are getting more and more important for organizations. Accordingly, the question arises in which industries these technologies can make a difference. This paper examines the use of drones in Swiss hospitals. A literature review is conducted outlining the most relevant flied of application for drone usage in healthcare. These use cases are then qualitatively rated by employees and patients of hospitals from different regions in Switzerland. Among others, the analysis revealed that employees and patients have strong concerns about drone usage in the hospital environment in the case drones provide diagnosis capabilities, but show less doubts if drones are used for delivery processes
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