Abstract:On a tilted plane T in three-space, skew distances are defined as the Euclidean distance plus a multiple of the signed difference in height. Skew distances may model realistic environments more closely than the Euclidean distance. Voronoi diagrams and related problems under this kind of distances are investigated. A relationship to convex distance functions and to Euclidean Voronoi diagrams for planar circles is shown, and is exploited for a geometric analysisis and a plane-sweep construction of Voronoi diagra… Show more
“…Following the notation of Renfrew and Level (1979) and Aichholzer et al (1999), let a be a single pixel on a raster map representing the whole study area. S is a set of p points (DHPs) on anisotropic region T with a ∈ T .…”
Section: Model Descriptionmentioning
confidence: 99%
“…The distance function on T is obtained by taking, for points p and a, the cumulative cost of transition (d a ) from a to p. The two coefficients z and k determine the balance between the size and distance of the DHP. The importance of distance increases in a linear manner while the importance of size increases exponentially (Aichholzer et al 1999). Thus, a larger DHP will be competitively stronger in relation to smaller ones, even at an increased distance.…”
This work presents an integrated method for the optimisation of a regional wood-energy supply network. The model is based on a scalar system that comprises a demand point (district heating plants (DHP)) and bio-energy sources (supply basin (SB)), each of which is related to a biomass terminal. The objective of optimisation is based on both technical-logistics and environmental parameters. An SB is defined by the anisotropic weighted Voronoi tessellation methodology. The parameters are then aggregated to a multiobjective analysis that includes the optimisation of variables and compromise programming approach. Results permit the identification of the best supply chain organisation and the determination of the agroforest energy districts where rural policy and intervention could be applied. The model was tested in the province of Florence (central Italy) to depict efficient scenarios for the fuelling of DHPs.
“…Following the notation of Renfrew and Level (1979) and Aichholzer et al (1999), let a be a single pixel on a raster map representing the whole study area. S is a set of p points (DHPs) on anisotropic region T with a ∈ T .…”
Section: Model Descriptionmentioning
confidence: 99%
“…The distance function on T is obtained by taking, for points p and a, the cumulative cost of transition (d a ) from a to p. The two coefficients z and k determine the balance between the size and distance of the DHP. The importance of distance increases in a linear manner while the importance of size increases exponentially (Aichholzer et al 1999). Thus, a larger DHP will be competitively stronger in relation to smaller ones, even at an increased distance.…”
This work presents an integrated method for the optimisation of a regional wood-energy supply network. The model is based on a scalar system that comprises a demand point (district heating plants (DHP)) and bio-energy sources (supply basin (SB)), each of which is related to a biomass terminal. The objective of optimisation is based on both technical-logistics and environmental parameters. An SB is defined by the anisotropic weighted Voronoi tessellation methodology. The parameters are then aggregated to a multiobjective analysis that includes the optimisation of variables and compromise programming approach. Results permit the identification of the best supply chain organisation and the determination of the agroforest energy districts where rural policy and intervention could be applied. The model was tested in the province of Florence (central Italy) to depict efficient scenarios for the fuelling of DHPs.
“…However, the flow of water also displaces the boat by At f (x, y), and hence the actual movement Du of the boat in time interval Zt is represented by .Au = atFvF + At f (x, y). (1) Consequently, the effective speed of the boat in the water flow is given by…”
Section: Boat-sail Distance and The Associated Voronoi Diagrammentioning
confidence: 99%
“…There are still many other distances. They include a geodesic distance [2,11,14], a collision-avoidance distance [3], a distance in a river [20], a skew distance [1], a peeper's distance [6], a crystal-growth distance [12,16], Karlsruhe distance [11], and the ski distance [11], and the Hausdorff distance [6].…”
A new concept called a boat-sail distance is introduced on the surface of water with flow, and it is used to define a generalized Voronoi diagram, in such a way that the water surface is partitioned into regions belonging to the nearest harbors with respect to this distance. The problem of computing this Voronoi diagram is reduced to a boundary value problem of a partial differential equation, and a numerical method for solving this problem is constructed. The method is a modification of a so-called fast marching method originally proposed for the eikonal equation. Computational experiments show the efficiency and the stableness of the proposed method.
“…Since then, there have been quite a number of research results on variations of this classical problem or related problems, e.g., the Voronoi diagrams [1,2,3,4,5,6,9,10,12,11]. A variation of the convex hull problem is defined as follows.…”
We consider the problem of computing the time convex hull of a set of points in the presence of a straight-line highway in the plane. The traveling speed in the plane is assumed to be much slower than that along the highway. The shortest time path between two arbitrary points is either the straight-line segment connecting these two points or a path that passes through the highway. The time convex hull, CH t (P ), of a set P of n points is the smallest set containing P such that all the shortest time paths between any two points lie in CH t (P ). In this paper we give a Θ(n log n) time algorithm for solving the time convex hull problem for a set of n points in the presence of a highway.
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