Kaçak göçmen akışının ihalar yardımıyla görüntülenebilmesi için enerji kısıtlı lokasyon rotalama modelleri

Unmanned Aerial Vehicles (UAVs) are aircrafts that are guided autonomously, by remote control, or both, and that are equipped with sensors, go-pro cameras, global positioning system (GPS), etc., depending on their purpose of use. Unencumbered by crew and the design-safety requirements of manned aircrafts, UAVs can be efficiently used in a wide range of military, commercial, and civil applications, where the last includes weather monitoring, forest fire detection, traffic control, and emergency search and rescue. The world has witnessed the biggest number of refugees on record at the end of 2016; an unprecedented 65.6 million people around the world were forced from home by conflict and persecution. Among them, the conflict in Syria was the world's biggest producer of refugees with about 5.5 million refugees. Many of these refugees tried to cross the Mediterranean Sea by overloaded and unsafe boats, and most of these trials ended in tragic ends with sunk boats and drowned people. There are lots of papers that have been written on different aspects of disaster management. None of these, however, have addressed the refugee problem, even though the International Federation of Red Cross and Red Crescent Societies (IFRC) have identified displaced populations as a disaster type. Our aim in this study is to model and solve a UAVs' surveillance problem. That is, we are given a set of target points that have to be visited once, a set of potential locations where stations to swap batteries or to refuel UAVs can be placed, and a main depot from which UAVs are initially launched and to where they eventually return. All these points form the node set of an undirected graph. We are also given a set of homogeneous UAVs. Now, our problem is to determine which of the potential stations to open and the routes of UAVs which minimize the total sum of operating costs of UAVs and opening costs of stations under several different sets of constraints. This problem type is known as the Location-Routing (L-R) problem in the OR/MS literature. However, due to the technical properties of UAVs, our mathematical formulation differs from the classic L-R formulation, as explained below. Our contributions to the literature can be explained as follows. Firstly, we propose the UAVs' surveillance problem as part of the risk mitigation phase of disaster management, where risk mitigation is defined by Federal Emergency Management Agency (FEMA) as the activities taken to prevent a disaster, reduce the chance of it happening, or reduce its damaging effects. We can achieve this by considering all target points to fill the danger area where many refugee boats have sunk so far. By surveying these points continuously, we aim at reducing the risk of boats passing through that area. Secondly, UAVs have very limited battery or fuel capacities. Hence, during their missions, their batteries have to be charged or swapped, or they have to be refueled. Therefore, different from the classic L-R formulation, we consider energy consumptions of UAVs in different flight statuses, and formulate the remaining consumable energies as part of our constraint sets. Moreover, in our problem, each subtour made by an UAV has to start and end at the main depot; hence, we formulate new subtour elimination constraints which eliminate all subtours that do not start and end at the main depot.