Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles
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Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles Jose Escribano Macias1,2 · Nils Goldbeck1 · Pei‑Yuan Hsu1 · Panagiotis Angeloudis1 · Washington Ochieng1 Received: 30 November 2018 / Accepted: 7 August 2020 / Published online: 18 August 2020 © The Author(s) 2020
Abstract Unmanned aerial vehicles (UAVs) have been increasingly viewed as useful tools to assist humanitarian response in recent years. While organisations already employ UAVs for damage assessment during relief delivery, there is a lack of research into formalising a problem that considers both aspects simultaneously. This paper presents a novel endogenous stochastic vehicle routing problem that coordinates UAV and relief vehicle deployments to minimise overall mission cost. The algorithm considers stochastic damage levels in a transport network, with UAVs surveying the network to determine the actual network damages. Ground vehicles are simultaneously routed based on the information gathered by the UAVs. A case study based on the Haiti road network is solved using a greedy solution approach and an adapted genetic algorithm. Both methods provide a significant improvement in vehicle travel time compared to a deterministic approach and a non-assisted relief delivery operation, demonstrating the benefits of UAV-assisted response. Keywords Relief optimisation · Endogenous uncertainty · Damage assessment · Unmanned aerial vehicles
The research was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) as part of the Sustainable Civil Engineering Centre for Doctoral Training (Grant number EP/L016826/1). * Jose Escribano Macias jose.escribano‑[email protected] 1
Department of Civil and Environmental Engineering, Imperial College London, London, UK
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Present Address: Exhibition Road, SW7 2AZ London, UK
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1 Introduction Disaster mortality has increased by 180% between 1994–2004 and 2004–2013, reaching 99,700 yearly deaths in the latter decade (CRED 2015). While three megadisasters (2004 Asian Tsunami, 2008 Cyclone Nargis and 2010 Haiti Earthquake) are the main contributors to this trend, their exclusion still yields a 17% rise in mortality over the same period. Another concerning factor is that climate change will increase the frequency of weather-related disasters. Efforts to protect vulnerable communities are undertaken by humanitarian organisations, who are increasing their relief operations budgets (Van Wassenhove and Pedraza Martinez 2012). As an indicative example, the United Nations (UN) World Food Programme (WFP) raised its spending by 60% between 2011 and 2017 (WFP 2017), exceeding $5 billion in 2016. In the aftermath of a natural disaster, the main immediate response operation consists of transporting and distributing essential goods for survival. This stage is essential for the long-term recovery and sustainability of the affected community, as survival rates reduce exponentially during the first 72 hours after
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