Fuzzy spatial network Voronoi diagram: a spatial decision support for transportation planning

Mabrouk, Aziz; Boulmakoul, Azedine; Bielli, Maurizio

doi:10.1504/ijssci.2009.026542

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Okabe in [6] summarizes the work done over the last decades on the network Voronoi diagrams that defines the metrics as weighted shortest path distances, to overcome the limitation of the planar Voronoi diagrams. Mabrouk in [15] suggests a fuzzy network Voronoi with a fuzzy weighted metrics. In the following we suggest partitioning the network using a fuzzy travel-time metrics.…”

Section: B Network Voronoi Partitioningmentioning

confidence: 99%

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Real-timefastest path algorithm using bidirectional point-to-point search on a Fuzzy Time-Dependent transportation network

Laarabi

Boulmakoul²,

Mabrouk

et al. 2014

2014 International Conference on Advanced Logistics and Transport (ICALT)

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International audienceNowadays management of information systems within the transport industry for effective and efficient decision making requires the use of latest technological development such real-time monitoring and traffic simulation. This will lead to the development of methods and algorithms, for instance, of fleet management, routing within a specified time windows and risk assessment. In this paper we will focus on proposing a method for finding itineraries that has the fastest travel-time on a time-dependent transportation network. It is modelled as a weighted graph, whose weight are time duration that depends on the time at which the road segment is traversed. This problem can be solved in polynomial time with a Single-Source algorithm, by the definition of some restrictions on the edge weights. However, its application on a graph with several millions nodes and edges is highly memory and time consuming. Alternatively, a bidirectional Point-to-Point path search, using A-star, offers far better performance. The novelty of the proposed approach is based on the modelling of an appropriate degree of dynamics of a real-world network by considering the fuzzy nature of the travel-time using Zadeh's fuzzy concept. In addition, we speed-up search by integrating a pre-computation phase, which consists in network partitioning using network Voronoi diagrams with implicit calculation of the lower-bound travel-time label for each node-to-border, border-to-border and border-to-node. Those labels should never overestimate the travel-time at any moment, to ensure the reliability of the suggested heuristic cost function

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Section: B Network Voronoi Partitioningmentioning

confidence: 99%

“…We define the Fuzzy Voronoi Graph (F-VG) by breaking down the graph to sub-graphs such that each sub-graph contains the closest -in terms of fuzzy fastest path -vertices and edges to predefined Voronoi seeds [15]. The Fig.…”

Section: Network Voronoi Diagram With a Fuzzy Fastest Path Metricsmentioning

confidence: 99%

Real-timefastest path algorithm using bidirectional point-to-point search on a Fuzzy Time-Dependent transportation network

Laarabi

Boulmakoul²,

Mabrouk

et al. 2014

2014 International Conference on Advanced Logistics and Transport (ICALT)

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Safest and shortest itineraries for transporting hazardous materials using split points of Voronoï spatial diagrams based on spatial modeling of vulnerable zones

Mabrouk

Boulmakoul

Karim

et al. 2017

Procedia Computer Science

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Fuzzy spatial network Voronoi diagram: a spatial decision support for transportation planning

Cited by 2 publications

References 9 publications

Real-timefastest path algorithm using bidirectional point-to-point search on a Fuzzy Time-Dependent transportation network

Real-timefastest path algorithm using bidirectional point-to-point search on a Fuzzy Time-Dependent transportation network

Safest and shortest itineraries for transporting hazardous materials using split points of Voronoï spatial diagrams based on spatial modeling of vulnerable zones

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