If outdoor positioning is widely treated and quite precise, positioning indoors or, more generally, in heterogeneous environments, as well as mobility prediction, requires important devices. New wireless technologies (e.g., Wi-Fi, Ultra Wide Band) combine the mobility of terminals with large bandwidth. Terminal mobility is one of the major pillars of applications attempting to become context-aware, and a large bandwidth enables new services such as multimedia contents streaming towards mobile terminals. Being context-aware and able to provide services in a mobile environment requires the knowledge of spatial and temporal data about the terminal. The key phase in the achievement of mobility management is the positioning process. We propose a layered positioning system based on a model combining a reference point-based approach with a trilateration-based one. Several layers of refinement are offered based on the knowledge of the topology and devices deployed. The more data are known, the better adapted to its area the positioning system can be.F. Lassabe (B) · P. Canalda · P. Chatonnay · F. Spies
Vehicle Routing Problems have been some of the most studied problems in combinatorial optimisation because they have many applications in transportation and supply chain. They are usually known as Vehicle Routing Problems or VRPs. The related literature is quite large and diverse both in terms of variants of the problems and in terms of solving approaches. To identify the different variants of routing problems, authors generally use initialisms, in which various prefixes and suffixes indicate the presence of different assumptions or constraints. But this identification based on initialisms is inefficient. For example, two variants of a problem may be identified by the same abbreviation, whereas different abbreviations may be assigned to the same problem. This paper proposes a new notation and a new formalism to identify and to classify instances of routing problems. This contribution aims at filling in the gaps of the current identification system. The goal is to allow everyone to position his work accurately in the literature, and to easily identify approaches and results comparable to his research. The proposed notation is inspired by the scheduling formalism. It has four fields (π/α/β/γ), respectively describing the type and horizon of the problem, the system structure, resources and demands, constraints and objectives to be optimized. 26 papers from the literature chosen
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