An exact algorithm for a stochastic bi-objective TSP with multiple drones with application in post-disaster rapid damage assessment
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
VeRoLog 2022: 8th meeting of the EURO Working Group on Vehicle Routing and Logistics Optimization
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Nowadays, drones are attracting increasing attention in the context of logistic applications. We address the case of rapid post-disaster damage assessment (RDA), which is critical in disaster relief for humanitarian organizations to plan an effective and efficient response. A prior investigation in the affected areas helps humanitarian organizations to be more prepared financially and operationally. RDA starts immediately after a disaster and is usually completed within a few days. On the one hand, the assessment should be performed as fast as possible due to the limited assessment horizon. On the other hand, since visiting all the affected nodes within a limited time may not be possible, a larger explored area of the affected region provides more accurate data for further relief operations. To this end, we consider a case when a truck and drones collaborate to improve the assessment operations exploiting the benefits of using both drone and truck in a sudden-onset disaster setting. This study proposes a scenario-based two-stage bi-objective variant of the traveling salesman problem with multiple drones (TSPMD). We consider a heterogeneous set of drones that differ in some characteristics, such as flight speed and battery capacity. Multiple drones can be launched simultaneously; however, the drone performs an assessment for exactly one affected node and returns to the truck, i.e., the truck must wait until all drones return. The first objective aims at maximizing the number of assessed affected nodes given their priority scores.
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