Abstract
This paper focuses on a modified Multi-Depot Unmanned Aerial Vehicle Routing Problem (MMDUAVRP). Comparing to classic multi-depot vehicle routing problem, our studied problem has no constraints to restrict the depot where the Unmanned Aerial Vehicle (UAV) departs and returns. This work aims to minimize the number of UAVs and total distance traveled by all UAVs. This problem is mathematically formulated in this paper and a heuristic-assignment based hybrid large neighborhood search(HLNS) is proposed to solve it. Extensive computational experiments are conducted to verify the performance of HLNS. The HLNS algorithm was first tested on Multi Traveling Salesman Problem which is a simplified version of the MMDUAVRP, and high quality solutions have been obtained. Experimental results by compared with CPLEX and other well-known algorithms suggest that our proposed algorithm provides better solutions within a comparatively shorter period of time. In addition, we also conduct sensitivity analysis on the location of depots and task points that may affect the total cost of solution.
Highlights
A PPLICATION of unmanned aerial vehicles(UAVs) have boomed in variety of domains which gained more and more attention
We studied a problem called modified multidepot Unmanned Aerial Vehicle (UAV) routing problem(MMDUAVRP), which is different to the classical multi-depot vehicle routing problem: the UAV may not return to the start depot after completing the task and just need to return to any depot
Our objective is to minimize the total distance traveled by all UAVs and the mathematical model of the problem is provided in this paper
Summary
A PPLICATION of unmanned aerial vehicles(UAVs) have boomed in variety of domains which gained more and more attention. LallaRuiz et al [21] presented an exact method based on a new integer programming formulation to address the Multi-Depot Open Vehicle Routing Problem(MDOVRP). Dondo et al [25] introduced a new model-based improvement methodology for the multi-depot heterogeneous-fleet VRPTW problem to enhance an initial solution through solving a series of Mixed Integer Linear Programming mathematical problems In their problem, exchanging and reordering of customers among routes are allowed. An algorithmic framework was proposed in OR which successfully solve three vehicle routing problems: the multi-depot VRP, the periodic VRP, and the multi-depot periodic VRP with capacitated vehicles and constrained route duration Their computational experiments obtained new best solutions for all available benchmark instances.
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